1. After Pharma Says “Interesting”: Why Interest Is Not Yet Momentum

2. The Diligence Readiness Test: What Pharma Needs Before It Can Go Deep

3. Organizing the Evidence: How Data Rooms Support Pharma Decisions

4. Why Two Pharma Companies Value the Same Asset Differently

5. Beyond the Upfront: What Pharma Is Really Negotiating

6. Structuring Around Uncertainty: When Options and Collaborations Work

7. Before the First Proposal: The Internal Work Behind Pharma Deal Terms ← You are here

8. The Deal Is Signed. Now the Partnership Has to Work.

Before Pharma Can Make a Proposal

For many biotech leadership teams, the period between diligence and the first proposal can feel quiet.

From the pharma side, that period may involve substantial internal work.

Teams are assessing the evidence, pressure-testing assumptions, aligning stakeholders, evaluating risks, and determining what kind of proposal the organization can credibly support.

A term sheet does not appear out of nowhere.

It is the outcome of internal alignment.

That distinction matters because a first proposal is not simply a number. It is a view of the asset, the uncertainty that remains, the rights needed, the structure required, and the level of commitment the organization believes it can defend.

Experienced counsel and advisors are essential in any transaction. This article is not legal advice, financial advice, or negotiation advice, and it is not intended to tell leadership teams what positions to take. The purpose is to help biotech CEOs understand how internal pharma alignment can shape the first visible proposal.

A Proposal Reflects More Than Price

A first proposal may look like economics and terms.

Behind it is a larger internal judgment.

The relevant questions vary by asset, stage, modality, deal type, and strategic context, but they may include:

How differentiated does the asset appear?

How much uncertainty remains?

How do internal reviewers interpret the evidence?

How much investment will be required after signing?

How much control does pharma believe it needs to execute?

Does the asset compete with internal alternatives?

How hard will the relationship be to govern?

How confident is the team in the partner company?

What can be defended internally?

These questions shape the proposal before it is written down. Pharma is not only deciding what to offer. It is deciding what it can defend.

That is why a proposal may sometimes feel conservative from the biotech side even when the pharma team remains genuinely interested. The interest may be real, but the organization still has to translate that interest into a structure, economics, rights, obligations, and governance that can survive internal scrutiny.

What Pharma Needs to Align Before a Proposal

Before a credible proposal can be sent, pharma teams often need to align across several dimensions. The exact process varies by company, asset, stage, and deal type, and not every dimension will apply equally in every situation. The underlying work, however, is similar: convert interest into a supportable position.

1. Diligence findings

Diligence does not only answer whether pharma is interested.

It helps determine what kind of proposal the organization can support.

If diligence increases confidence, the proposal may reflect that. If diligence identifies unresolved questions, the proposal may also reflect that through valuation, staged economics, option structures, milestones, scope, obligations, governance, termination provisions, manufacturing terms, or IP-related protections.

The clearer the evidence, the easier it is for internal advocates to support a more confident position.

That does not mean every uncertainty must be eliminated. It does mean the remaining uncertainties need to be understood, framed, and connected to the proposed structure.

A data gap is not always fatal.

An unmanaged or poorly understood gap is harder to carry forward.

2. Cross-functional stakeholder alignment

A proposal often reflects alignment across multiple functions.

Business development may lead the transaction process, but a serious proposal can be shaped by many functions. Depending on the asset, stage, and proposed transaction, stakeholders may include BD, search and evaluation, R&D, clinical development, regulatory, CMC, IP, commercial, finance, legal, governance bodies, and senior leadership.

Each function may see a different part of the risk, and not every function will be equally relevant in every deal.

For example, CMC concerns may influence manufacturing obligations, technology transfer, timelines, or milestones. IP concerns may affect scope, royalty duration, royalty reductions, or downstream economics. Clinical concerns may influence development milestones, option triggers, or the evidence needed before a larger commitment. Commercial concerns may influence valuation assumptions. Legal concerns may influence risk allocation, termination, and contracting structure. Finance concerns may influence upfront payment, milestones, and payment timing.

The term sheet is often a cross-functional compromise before it becomes an external proposal.

That is not a weakness in the process.

It is part of how a large organization turns multiple expert views into one position.

3. Valuation assumptions

In an earlier article, I wrote that value is buyer-specific. The same asset can have different value to different pharma companies because each company is solving a different strategic, portfolio, capability, and risk-allocation problem.

Before a proposal is sent, those value assumptions have to become deal logic.

Depending on the opportunity, assumptions may include patient population, differentiation, probability of success, development timeline, development cost, market access, competitive timing, IP durability, manufacturing cost, expected commercial adoption, or other factors relevant to the asset.

When assumptions change, deal terms change.

What looks like a pricing disagreement may actually be an assumptions disagreement.

One party may be assuming a broader patient population. Another may be assuming a narrower one. One may believe differentiation will matter commercially. Another may believe the future market will be more crowded. One may assign greater confidence to the development path. Another may discount value because major uncertainties remain.

This is why valuation conversations can become difficult. The visible debate may be about economics. The underlying debate may be about what the asset can become, how likely that future is, how much it will cost to get there, and who should bear which risks along the way.

4. Risk allocation

Deal structure is often the language risk uses to express itself.

Depending on the risk, the proposal may reflect that uncertainty in different ways. High uncertainty may move more value into milestones. Unresolved technical risk may support an option or structured collaboration. CMC risk may bring more attention to manufacturing obligations, technology transfer, or supply provisions. IP risk may affect royalty terms, scope, or downstream economics. Governance risk may make decision rights and control provisions more important.

This is not simply about shifting burden.

It is about designing a structure that reflects what is known, what remains uncertain, and what each party is prepared to own.

From the biotech side, some terms may feel cautious or restrictive. From the pharma side, they may reflect the organization’s view of the remaining risk and what it can responsibly support.

The better the parties understand the risk, the more coherent the structure can become.

5. Control and governance concerns

From the outside, control provisions can feel like power.

From the inside, they may be viewed as accountability for execution.

Depending on the deal, a pharma partner may seek control or governance rights because it expects to fund development, manage regulatory strategy, oversee CMC, make safety decisions, control IP prosecution, guide commercialization, or commit internal resources after signing.

That does not mean every control request is equally important or appropriate in every deal. It does mean control should be understood in context.

If pharma is accountable for execution, it may need decision rights that allow it to execute. If biotech is retaining meaningful responsibilities, it may need enough visibility and participation to manage its own obligations and future strategy.

The proposal may therefore reflect a negotiated view of who is best positioned to make which decisions, who carries which risks, and how disagreements should be handled.

Governance is not decoration.

It is how the relationship is expected to operate under pressure.

6. Internal defensibility

Internal defensibility is often the quiet center of the process.

A proposal is not only what one deal team wants.

It is what that team believes it can carry through the organization.

Internal champions may need to answer:

Why this asset?

Why now?

Why this partner?

Why these economics?

Why this structure?

Why these rights?

Why this level of risk?

Why this opportunity over other uses of capital, attention, and organizational capacity?

This is where the quality of the evidence, the clarity of the strategic rationale, the credibility of the development path, and the practicality of the deal structure all come together.

A proposal has to be supportable not only externally, but internally.

That is why internal defensibility matters.

It is the bridge between interest and action.

7. Alternatives and opportunity cost

A proposal also reflects what else pharma could do.

Depending on the strategic context, the organization may be weighing internal programs, other external assets, different collaboration structures, alternative uses of capital, or the option to wait for more data.

The offer reflects not only the asset in front of pharma, but the alternatives behind it.

This does not mean the asset lacks merit. It means the asset is being evaluated inside a broader set of choices.

A strong proposal must therefore answer not only:

Is this interesting?

But also:

Why this opportunity, in this structure, now?

That is a different bar.

Why “Just Send a Term Sheet” Misses the Internal Work

From the outside, it can be tempting to think: if pharma is interested, why not just send a term sheet?

Sometimes the answer is that interest has not yet become internal alignment.

Diligence may still be unresolved. Key functions may not yet be aligned. Valuation assumptions may not be stable. The governance path may not be clear. Internal sponsorship may still be forming. Risk allocation may not be agreed. Leadership may still need to approve direction.

Delay is not always lack of interest.

It may reflect unresolved internal alignment.

But founders should not assume delay is positive either. Silence does not necessarily mean momentum. A long process may reflect active work, unresolved disagreement, competing priorities, or declining urgency.

The more useful question is:

What decision is still being formed?

That question is better than trying to read every pause as good news or bad news. It keeps the focus on decision quality, not emotional weather-reading.

How CEOs Can Support Decision Quality

The goal is not to negotiate before the negotiation.

The goal is to reduce avoidable ambiguity.

Biotech CEOs can support decision quality by making the evidence easy to evaluate, clarifying the asset thesis, naming key risks honestly, explaining what evidence has reduced uncertainty, answering cross-functional questions clearly, and distinguishing what is known, what is unknown, and what is planned.

This is not about overselling.

In fact, overselling can be counterproductive. If every risk is minimized, internal reviewers may become less confident, not more. A clear articulation of risk often builds more trust than a polished narrative that avoids uncertainty.

Every diligence interaction can inform confidence.

The scientific discussion, the data room, the quality of responses, the way gaps are framed, the company’s ability to explain tradeoffs, and the consistency of the leadership team’s story can all influence whether internal advocates can carry the opportunity forward.

The best support a biotech company can provide is clarity.

Not pressure.

Not premature negotiation.

Clarity.

What Not to Overinterpret

Internal alignment is not always visible from the outside.

Do not overinterpret:

• slow movement as lack of interest

• fast movement as full internal alignment

• a proposal as final consensus

• tough terms as bad faith

• silence from one stakeholder as organizational disinterest

The process can be active even when it is not visible.

It can also be stalled even when conversations remain cordial.

The point is not to decode every signal perfectly. The point is to understand that the first proposal is shaped by internal work that may be only partially visible to the company receiving it.

CEO Actions

Before expecting or evaluating a proposal:

• Treat diligence as part of how pharma builds internal clarity, not only as a pass/fail screen.

• Make the evidence, risks, and open questions easy for internal advocates to explain.

• Understand which assumptions are most likely to affect value, structure, and control.

• Ask what additional evidence would improve decision quality without trying to force premature agreement.

• Align your board on the possibility that pharma’s first proposal may reflect internal risk allocation, not simply negotiating posture.

• Use counsel and advisors to evaluate the proposal as the product of assumptions, not just as a set of numbers.

Executive Takeaway

A term sheet is not created in isolation. It is the visible output of internal work around evidence, risk, value, structure, and internal defensibility.

For biotech leadership teams, the task is not to game that process or negotiate before the negotiation. It is to understand that every diligence interaction can affect internal clarity and confidence.

Pharma is not only deciding what to offer.

It is deciding what it can defend.

Once the proposal becomes a contract, the work changes again. The relationship moves from negotiation to execution. Governance begins. Obligations become operational. Data, decisions, timelines, and trust begin to matter in a different way.

That is the subject of the final article.

1. After Pharma Says “Interesting”: Why Interest Is Not Yet Momentum

2. The Diligence Readiness Test: What Pharma Needs Before It Can Go Deep

3. Organizing the Evidence: How Data Rooms Support Pharma Decisions

4. Why Two Pharma Companies Value the Same Asset Differently

5. Beyond the Upfront: What Pharma Is Really Negotiating

6. Structuring Around Uncertainty: When Options and Collaborations Work← You are here

7. Before the First Proposal: The Internal Work Behind Pharma Deal Terms

8. The Deal Is Signed. Now the Partnership Has to Work.

The Appeal of Structuring Around Uncertainty

When uncertainty remains high, a full license or acquisition may be premature.

But uncertainty still needs a structure.

The biotech may need validation, expertise, and time to generate additional data. Pharma may need earlier access, more information, and a way to stay close to a strategically relevant asset before making the full downstream commitment.

At its best, an option or structured collaboration helps both sides share risk and generate better evidence. At its worst, it defers hard alignment questions until the parties are more constrained.

That distinction matters. A structure that looks attractive at signing can create friction later if the parties have not agreed on what uncertainty is being resolved, what work must be done, what rights are restricted, and what future decision the structure is meant to support.

The purpose is not to help either side “win” the structure.

The purpose is to help both sides understand whether the structure is fit for the decision it is supposed to support.

Experienced counsel is essential in any option-based or collaboration-based transaction. This article is not legal advice, financial advice, or a complete list of the terms that may appear in an option agreement, research collaboration, license agreement, or definitive contract. It is also not intended to tell leadership teams which terms to accept. The purpose is narrower: to help biotech leadership teams understand the business questions they should ask before treating an option or structured collaboration as the right path forward.

Options Are One Tool, Not the Only Tool

Option deals are one way to manage uncertainty, but they are not the only way.

Depending on the asset, stage, modality, and strategic question, parties may also use research collaborations, feasibility studies, material transfer agreements, sponsored research, staged licenses, equity investments, or research collaborations with licensing terms already negotiated or partially negotiated.

A research collaboration with pre-negotiated licensing terms can serve a similar purpose when the parties want to generate data together before a full license decision. The same is true for a research collaboration with an option to license, where the collaboration period is intended to produce evidence that informs a later decision.

The important point is not the label.

The structure should follow the uncertainty being addressed, not the other way around.

If the uncertainty is technical, the structure should support the work needed to answer the technical question. If the uncertainty is translational, the structure should support evidence generation that helps bridge toward humans. If the uncertainty is manufacturing, the structure should clarify what process work, characterization, or feasibility work is needed. If the uncertainty is clinical, the structure should define what evidence would make a future development commitment more credible.

The wrong structure can create the appearance of progress without resolving the uncertainty that matters.

The right structure turns uncertainty into a decision plan.

An Option Is a Decision Structure

An option or structured collaboration should be understood as a structure around a future decision.

At minimum, it should make explicit: what uncertainty is being resolved, what data will be generated, who funds and controls the work, who contributes expertise, who owns or can use the data, what rights are restricted during the option or collaboration period, and what happens if the option is exercised, expires, or the collaboration does not convert.

The option period should not be a waiting room.

The collaboration period should not be a holding pattern.

Both should be designed paths to a decision.

That is the difference between structuring around uncertainty and merely postponing disagreement. A well-designed structure gives both parties a clearer way to learn. A poorly designed one can leave the parties with more data, less clarity, and the same unresolved disagreement.

What a Good Structure Makes Explicit

A good option or structured collaboration does not need to answer every future question. It should, however, make the next decision easier to understand.

Several elements matter.

1. The uncertainty being resolved

An option or collaboration should be tied to a specific uncertainty or set of uncertainties.

That uncertainty may relate to target validation, translational relevance, the PK/PD relationship, efficacy in a defined model, toxicology or safety window, manufacturability, biomarker strategy, clinical feasibility, regulatory path, or early clinical signal, depending on stage.

The exact question will vary by asset. A preclinical small molecule, antibody, genetic medicine, cell therapy, platform-derived asset, or Phase 2-ready program will not require the same evidence.

But the discipline is the same.

If the parties cannot name the uncertainty, they may not be aligned on why the structure exists.

That is where trouble can begin. The biotech may believe the collaboration is validating the asset. Pharma may see it as a limited feasibility exercise. The board may see it as a path to a future license. The internal pharma team may see it as a way to decide whether deeper review is justified.

Those are not the same thing.

A good structure makes the purpose explicit.

2. The future decision point

A good structure does not simply create time. It creates a decision point.

That decision point may be data-based, time-based, milestone-based, or discretionary. It may occur after completion of a workplan, delivery of a defined data package, achievement of a technical milestone, or review by a governance committee.

The key is clarity.

What triggers the option decision, license decision, or next-stage commitment?

What evidence package will be reviewed?

Who decides whether the package is complete?

Is there a required decision window?

What happens if the evidence is promising but incomplete?

These questions matter because ambiguity can create friction precisely when the parties most need alignment. If the biotech believes the threshold has been met and pharma believes the package remains insufficient, the structure has not done enough work.

The future decision should be visible from the beginning, even if the outcome is uncertain.

3. The workplan, funding, and pharma contribution

During an option or research collaboration, both sides are contributing something valuable before the larger downstream commitment is made.

Biotech may contribute access, data, strategic optionality, and sometimes exclusivity. Pharma may contribute funding, expertise, diligence capacity, translational judgment, development input, legal support, contracting effort, governance attention, and internal advocacy.

From the biotech side, the structure may look like validation and a path to a future partnership. From the pharma side, it may represent a meaningful investment of time, attention, expertise, organizational capacity, and legal and contracting resources before the evidence supports a full license or acquisition.

Pharma is not only buying time.

It may also be investing in the work needed to make a later decision credible.

A good structure should clarify what work will be done, who funds it, who performs it, who controls protocol design, what expertise pharma will contribute, and what happens if the work costs more or takes longer than expected.

The better question is whether the economics, rights, restrictions, expertise, and workplan fairly reflect what each side is contributing and what decision the structure is meant to support.

4. Control and governance during the option or collaboration period

Control during the option or collaboration period can be delicate.

The biotech may remain responsible for advancing the asset. Pharma may want input into study design, data generation, translational plans, CMC work, or other activities that could affect the future decision.

That is not surprising. The more pharma needs the data to support a future decision, the more it may care how the data are generated.

The goal is not governance for its own sake.

The goal is a process that allows decision-relevant work to proceed with enough alignment to matter.

5. Exclusivity and strategic flexibility

Exclusivity is one of the most important tradeoffs in an option or structured collaboration.

From pharma’s perspective, exclusivity may be part of what justifies investing time, funding, expertise, legal support, contracting effort, governance attention, and organizational resources before a full license or acquisition. If pharma is helping shape the data package, contributing internal expertise, and preserving capacity for a future decision, it may want confidence that another party will not step in after that work has increased the asset’s value.

From biotech’s perspective, exclusivity may reduce competitive tension and strategic flexibility during a critical period.

Both perspectives are understandable.

The right question is not whether exclusivity is good or bad.

It is whether the restrictions are proportionate to what both parties are contributing and what decision the structure is meant to support.

That requires asking practical questions. Is the biotech restricted from talking to others? Does exclusivity cover the asset, target, field, modality, territory, or platform? How long does the restriction last? Are there carve-outs? Does the structure affect financing, partnering, or strategic flexibility? What happens if the option is not exercised or the collaboration does not lead to a license?

Exclusivity can be reasonable.

It can also be costly.

The difference depends on scope, duration, value received, and what future paths remain open.

6. Economics if the option is exercised or the collaboration converts

A structure can reduce uncertainty about the science while leaving uncertainty about the deal.

That is useful to understand before signing.

The future deal terms may be fully pre-negotiated, partially pre-negotiated, or left open. Each approach has tradeoffs.

If the exercise price, milestones, royalties, rights, scope, territory, field, obligations, and development commitments are largely pre-negotiated, the parties may have greater certainty about the future transaction. But they may also be setting terms before the future data are known.

If many terms remain open, the parties may preserve flexibility. But they may also be moving important questions to a later moment, when the information balance and available paths may look different.

Neither approach is universally right.

The question is whether the post-exercise or post-collaboration path is clear enough to support the decision the structure is meant to enable.

If the post-exercise terms are not clear enough, the structure may defer negotiation rather than solve it.

7. Consequences if the option is not exercised or the collaboration does not convert

This is one of the most important parts of the structure.

It is also one that can be underappreciated at signing, when everyone is focused on the hoped-for future transaction.

What happens if the option is not exercised?

What happens if the collaboration does not lead to a license?

Can the biotech continue development?

Can it partner with others?

Who owns or can use data generated during the option or collaboration period?

Are there restrictions on future transactions?

Are there repayment obligations, license-back rights, residual rights, or ongoing obligations?

Are there any reputation or signaling effects?

How quickly does the biotech regain freedom to operate strategically?

A non-exercised option should not leave the biotech trapped in a narrower strategic position without a clear path forward.

A collaboration that does not lead to a license should still leave the biotech with a usable outcome and a path forward.

The goal is not to assume failure.

The goal is to make sure the company can keep moving if the future transaction does not occur.

Why Validation Still Has a Cost

Validation from a pharma relationship can be meaningful.

It may strengthen credibility, help focus the development path, improve the evidence package, and give the biotech leadership team a clearer sense of what a sophisticated partner would need to see before a larger downstream commitment.

Those are real benefits.

But validation is not free for either side.

For biotech, the tradeoffs may include exclusivity, timing flexibility, information rights, future strategic flexibility, and sometimes the ability to engage other partners during a critical period.

For pharma, the cost is also real. Even before a full license or acquisition, pharma may devote internal scientific time, translational judgment, development input, CMC, regulatory, commercial, and BD expertise, diligence capacity, governance attention, legal support, contracting effort, and internal advocacy.

That is why structure matters.

Importantly, an option or research collaboration does not necessarily weaken the biotech’s position. It may strengthen it if the collaboration produces convincing validation data, clarifies the development path, reduces major technical uncertainty, or generates evidence that other potential partners would also find compelling.

The risk is not the structure itself. The risk is accepting meaningful restrictions without generating evidence that improves decision quality, or leaving the future transaction path unclear after meaningful work has been done.

The right question is not whether the option payment or collaboration funding is “enough” in isolation. It is whether the full package of validation, funding if any, pharma expertise, internal resource commitment, restrictions, future economics, and decision rights makes sense for the company’s strategy.

Validation is valuable.

But validation still has a cost.

Boards May See Validation. Management Must See the Tradeoff.

Boards, especially venture-backed boards, may view an option or research collaboration with pre-negotiated license terms as validation and a path to extend the company’s strategic runway.

That may be true.

But boards and management should also align on what strategic flexibility is being restricted, what future process is being foreclosed, and whether the post-option or post-collaboration path is clear enough to justify those restrictions.

This is not about telling the board no.

It is about aligning the board on the tradeoff before the company becomes constrained.

A venture-backed board may focus on validation, runway extension, or the perceived signal of pharma interest. Management also has to think about the operating reality: what the company can and cannot do during the option period, what happens if the future transaction does not occur, and whether the structure improves or narrows the company’s next set of choices.

The best time to align on those tradeoffs is before the structure is signed.

Not after the company discovers that the structure limits the path it now wants to pursue.

Why Pharma May Prefer an Option or Structured Collaboration

From pharma’s perspective, an option or structured collaboration can justify committing time, expertise, legal support, contracting effort, governance attention, and funding before the evidence supports a full license or acquisition.

The biology may be promising but not sufficiently validated. The translational, CMC, safety, or clinical path may still need sharper definition. The strategic fit may be real, but internal conviction may still be forming.

In that setting, a structured collaboration can create a disciplined way to learn. It may allow pharma to gain early access, shape the data package, contribute expertise, preserve a future right, manage technical uncertainty, and reduce the risk of overcommitting before the evidence is mature.

Biotech leadership teams should understand that pharma’s interest in an option is often not simply a desire to delay commitment. It may reflect the need to make a later commitment more defensible.

A good structure helps both parties generate the evidence needed for a better decision. A poor structure gives one or both parties time without clarity.

What Not to Overinterpret

Option and collaboration signals matter.

But the structure determines what they mean.

Do not overinterpret:

• an option as a guaranteed future deal

• option or collaboration funding as equivalent to full partnership commitment

• pharma input rights as automatic loss of control

• exclusivity as always unacceptable

• a non-exercised option as proof the asset has no value

The better question is not whether the signal is positive.

The better question is what the structure allows the company to do next.

CEO Actions

Before entering an option or structured collaboration:

• Define what uncertainty the option or collaboration is intended to resolve.

• Clarify the evidence package needed for the future decision.

• Understand what rights are restricted during the option or collaboration period.

• Align with your board on the tradeoff between validation, pharma expertise, internal resource commitment, exclusivity, and strategic flexibility.

• Pressure-test what happens if the option is not exercised or the collaboration does not lead to a license.

• Negotiate the post-exercise or post-collaboration path carefully, not just the near-term funding.

Executive Takeaway

Options and structured collaborations can be elegant when they are designed around a clear future decision. They can help both parties share uncertainty, generate better evidence, and avoid premature full commitment.

But they are not automatically founder-friendly or pharma-friendly. They are structures that may trade some present flexibility for the possibility of better future information and a larger downstream transaction.

For biotech leadership teams, the central question is not:

Did we get an option?

It is:

What decision is this structure designed to support, what are both parties contributing, what tradeoffs are we accepting during the option or collaboration period, and what happens if the future transaction does not occur?

Options and structured collaborations also highlight a broader truth: pharma’s negotiating position often begins forming before a term sheet is ever sent. Diligence findings, internal alignment, valuation assumptions, risk allocation, governance concerns, and confidence in the future decision all shape what the company is prepared to offer.

That hidden negotiation is the subject of the next article.

1. After Pharma Says “Interesting”: Why Interest Is Not Yet Momentum

2. The Diligence Readiness Test: What Pharma Needs Before It Can Go Deep

3. Organizing the Evidence: How Data Rooms Support Pharma Decisions

4. Why Two Pharma Companies Value the Same Asset Differently

5. Beyond the Upfront: What Pharma Is Really Negotiating ← You are here

6. Structuring Around Uncertainty: When Options and Collaborations Work

7. Before the First Proposal: The Internal Work Behind Pharma Deal Terms

8. The Deal Is Signed. Now the Partnership Has to Work.

The Headline Is Not the Deal

After valuation discussions begin, biotech leadership teams often focus on the most visible numbers: upfront payment, total potential deal value, milestones, and royalties.

Those numbers matter.

But they are not the whole deal.

From inside a pharma organization, the negotiation is often broader. The question is not only, “What is this asset worth?” The question is, “How should value, risk, control, obligations, and future optionality be allocated?”

The market remembers the headline.

The parties live with the terms.

A deal that looks attractive in headline economics may be less attractive if the rights, obligations, governance, manufacturing responsibilities, or termination provisions constrain future value. The reverse can also be true. A deal with more modest upfront economics may be strategically valuable if it preserves important rights, funds critical work, aligns incentives, and creates a credible path to future value inflection.

Experienced counsel is essential in any transaction. This article is not legal advice, financial advice, or a complete list of all legal and business terms that may appear in a term sheet or definitive agreement. It is also not intended to tell leadership teams which terms to accept. The purpose is narrower: to help biotech CEOs understand why certain terms matter from a business and strategic perspective, which questions they should know to ask, and where expectations may need to be aligned among management, the board, counsel, and the potential pharma partner.

That last point matters. In many negotiations, biotech leadership teams are not only negotiating with pharma. They are also managing internal expectations. A board consisting of venture capital investors may push for split indications, co-development rights, co-commercialization, broad information rights, strong diligence obligations, or tight commercially reasonable efforts language. Those asks may be understandable from the biotech’s perspective, but they may not always be realistic in the context of a global pharma partnership. Some may be difficult for a global pharma partner to accept, depending on the asset, stage, deal structure, investment required, clinical development burden, and strategic rationale.

The goal is not to enter a negotiation asking for everything.

The goal is to understand which terms truly matter, why they matter, and where the other side is likely to hold firm.

Economics Describe Value. Terms Allocate It.

The upfront is important because it reflects immediate commitment. It may also reflect consideration for the de-risking of the asset to date, including the extent and quality of the evidence generated. But the terms determine the operating reality of the partnership.

Who controls development?

Who funds which work?

Who decides whether to continue?

What rights does each party keep?

What happens if the data are ambiguous?

What happens if manufacturing becomes difficult?

What happens if priorities change?

These questions can matter as much as the headline economics.

Economics express value. Terms determine how that value can be realized, protected, shared, constrained, or lost.

An upfront payment reflects one part of value. It is influenced by many factors, including the breadth of rights being granted, the level of control being transferred, the amount of future uncertainty being assumed, and the extent to which the asset has been de-risked. The quality of that de-risking matters too. A data package that clearly reduces the most important uncertainties may support a different upfront than one that is larger but less decision-relevant.

Milestones reflect future risk reduction or achievement. Royalties and commercial milestones reflect participation in downstream success. Scope determines where value can be captured. Rights determine who can act. Obligations determine who must act. Governance determines how decisions are made. Termination provisions determine what happens when circumstances change.

This is why a term sheet is not just a financial proposal.

It is the first version of the operating relationship.

The Terms Behind the Headline

Pharma is not negotiating a number in isolation. It is negotiating the structure of a potential relationship.

The specific terms will depend on the asset, stage, modality, indication, deal type, and parties involved. This article is not exhaustive. A real agreement will include many additional legal, business, operational, tax, compliance, accounting, confidentiality, publication, audit, representation, warranty, indemnity, assignment, change-of-control, and dispute-related provisions that require experienced counsel and careful business review.

But several categories are especially important for biotech leadership teams to understand because they shape how the partnership actually works.

1. Scope of Rights

The first question is: what exactly is being granted?

This may include asset-specific rights, platform rights, field of use, indication scope, target scope, modality scope, territory, exclusivity, non-exclusive research rights, sublicense rights, and rights to improvements or follow-on products, depending on the deal.

Scope defines the playing field.

Scope is where ambition and constraint meet.

A broad grant can create attractive economics because it gives the pharma partner more control and more ways to create value. But a broad grant can also limit the biotech company’s future strategic flexibility.

For example, granting broad rights across all fields, all territories, or all related targets may be appropriate in some contexts. In others, it may limit the company’s ability to pursue adjacent programs, engage other partners, develop related assets, or preserve future strategic options.

The business question is not only:

What are we granting?

It is also:

What future strategy are we enabling or foreclosing?

That is why scope should be treated as a strategic question, not merely a legal definition.

2. Control Rights and Strategic Flexibility

Each party cares not only about what is transferred, but what remains available for future strategy.

This includes rights the biotech keeps, rights pharma controls, field-limited rights, territory-limited rights, indication splits, co-development or co-commercialization rights, rights to pursue adjacent programs, rights to continue internal research, platform use rights, restrictions on competing programs, and future target or product nomination rights where relevant.

Preserved rights are not leftovers.

They can be part of the company’s future strategy.

For biotech leadership teams, this matters because early deals can shape the company’s future perimeter. A company may be solving for capital, validation, expertise, or near-term execution support, but it should also understand what the transaction means for the next asset, the next indication, the next platform application, or the next financing.

This is also where internal expectations need discipline. A board may want the company to retain co-development rights, co-commercialization rights, regional rights, or rights to split indications. Those requests can be strategically understandable from the biotech’s point of view. But they may not be acceptable to a pharma partner if the partner is expected to fund major development, including the significant cost and risk of clinical trials, absorb execution risk, manage regulatory strategy, scale manufacturing, or commit commercial infrastructure.

For pharma, control rights matter because the partner may need enough freedom to develop, invest, manufacture, commercialize, and protect the asset without constant ambiguity.

Both sides are solving for flexibility, but not always the same kind.

The art is understanding which control points matter most, which requests are realistic, and which tradeoffs are acceptable.

3. Payments and Staged Economics

The upfront is only one economic component.

Other economic terms may include research funding, FTE support, development milestones, regulatory milestones, commercial milestones, royalties, royalty duration, royalty reductions, sales thresholds, and cost-sharing arrangements.

Staged economics are how parties share uncertainty over time.

This connects directly to valuation. If value is risk-adjusted, economics often become staged. The more uncertainty remains, the more the parties may rely on milestones, contingent payments, research support, option payments, or success-based economics rather than placing all value in the upfront.

The upfront is also influenced by the maturity and quality of the evidence. An asset with strong, decision-relevant de-risking may support a different upfront than one where important uncertainties remain unresolved. This is not only about how much data exist. It is about whether the data answer the questions that most affect conviction.

This is not necessarily a bad outcome.

A large upfront can be attractive, but it may come with broader rights, stronger control provisions, or greater strategic constraints. A smaller upfront may be acceptable if it funds important work, preserves meaningful future options, and creates a path to downstream value.

Large total deal value should also be interpreted carefully. Announced deal values often include milestones that are uncertain, distant, or contingent on significant development, regulatory, and commercial success.

The question is not only:

What is the total headline value?

It is:

How much value is certain, how much is contingent, what must happen to earn it, and who controls the work required to get there?

4. Obligations, Responsibilities, and Commercially Reasonable Efforts

This is one of the most important parts of a deal and one that biotech leadership teams should not treat as boilerplate.

A responsibility describes who is expected to do the work.

An obligation creates accountability.

That distinction matters. A party may be responsible for development activities, but the agreement must define what level of effort, funding, timing, reporting, and decision-making is required. Without that clarity, the parties may have different expectations after signing.

Commercially reasonable efforts is especially important.

It is not just legal language. It is one of the places where the parties define what continued commitment should look like when the future becomes uncertain.

The specific meaning of commercially reasonable efforts depends on the agreement, the context, and the negotiated standard. That is why experienced counsel matters. But CEOs should still understand the business purpose of the concept.

At a high level, commercially reasonable efforts can influence how diligently a party must pursue development, regulatory approval, commercialization, or other agreed activities. It can interact with development plans, budgets, timelines, governance processes, reporting obligations, and termination rights.

This is also an area where global pharma partners may hold strong positions. A pharma company may want flexibility to make decisions based on emerging data, safety findings, regulatory feedback, manufacturing complexity, competitive changes, commercial viability, portfolio priorities, or internal resource allocation. That flexibility is not always a negotiating tactic. In many cases, it reflects the reality that the asset will enter a larger portfolio where decisions must be made over time under changing conditions.

A biotech company may want confidence that the asset will not be deprioritized without meaningful effort to advance it. That concern is also legitimate.

The business question is how the agreement balances those concerns.

For biotech leadership teams, this language matters because it may determine what happens after signing, when the asset enters the partner’s portfolio and must compete for continued attention, resources, and execution.

Will the partner be required to advance the program according to an agreed plan?

What happens if the partner’s strategy changes?

What happens if competing internal programs emerge?

What happens if data are mixed but not definitively negative?

What reporting will allow the biotech to understand progress?

These questions are not abstract. They go directly to whether the economic promise of the deal has a credible path to becoming real.

At the same time, biotech leadership teams should recognize that asking for absolute commitments, rigid timelines, or highly restrictive effort standards may not be realistic in many pharma partnerships. A board may want maximum protection against deprioritization. Pharma may resist language that limits its ability to make portfolio, regulatory, safety, or commercial decisions as facts evolve.

The CEO’s job is not to eliminate that tension.

It is to understand it well enough to manage the discussion with counsel, the board, and the potential partner.

CEOs do not need to draft this language themselves. They do need to understand what business behavior the language is intended to create.

A deal can look strong economically and still be weak operationally if obligations are unclear, effort standards are unrealistic, or governance does not provide visibility into whether the agreed work is actually being done.

5. Manufacturing and Supply

Manufacturing and supply can look technical.

They are strategic.

They can shape timing, cost, quality, control, scalability, and whether the partnership can execute.

Depending on the asset and deal structure, the agreement may need to address who manufactures, who controls process development, who manages technology transfer, who supplies bulk drug substance, who handles formulation, who manages fill-finish, who owns quality systems, who performs release testing, who funds supply, and who bears responsibility for manufacturing failures or delays.

For early-stage companies, these questions may feel premature.

They are often not.

Manufacturing decisions can determine whether development timelines are realistic. They can affect regulatory readiness. They can shape cost of goods. They can determine who controls process improvements. They can influence whether clinical supply is available when needed. They can become especially important for biologics, genetic medicines, cell therapies, complex formulations, and other modalities where manufacturing is not a routine afterthought.

Manufacturing is not only operational.

It can shape control, timing, cost, quality, and risk.

If the product cannot be made reliably, even a well-structured deal will struggle to create value.

That does not mean every manufacturing question must be fully resolved at signing. It does mean the parties should understand who owns the problem, who funds the work, who controls improvements, and how manufacturing risk affects future milestones, obligations, and timelines.

6. IP Prosecution, Enforcement, Know-How, and Improvements

IP is not only a diligence topic.

It becomes part of how the deal operates.

The agreement may need to address who controls patent prosecution, who pays for prosecution, who enforces patents, who controls defense, who owns improvements, how know-how is transferred, how trade secrets are protected, and what happens if patent coverage changes.

These terms matter because valuation often assumes durable exclusivity.

The agreement needs to define how that exclusivity will be protected and what happens if it weakens.

For example, royalty rates, royalty duration, milestones, and downstream sharing of upside may depend on patent coverage, regulatory exclusivity, know-how, or the presence of generic or biosimilar competition. If patent claims narrow, expire, are challenged, or fail to cover a future product, the economic assumptions may change. When those assumptions change, valuation can change as well, including how parties think about milestones, royalties, and downstream participation in success.

Similarly, improvements can become strategically important. If one party develops a manufacturing improvement, new formulation, new use, new biomarker, or follow-on product concept, the agreement should clarify who owns it, who can use it, and how it affects the broader relationship.

In some early-stage or platform-based deals, know-how may be as important as issued patent claims because it is part of what enables the technology to be practiced.

IP terms determine how future value is protected, not just how existing value is described.

This is where legal precision and business strategy meet.

7. Governance, Dispute Resolution, and Termination

Governance matters because the future will not unfold exactly as the term sheet imagines.

Data may be mixed. Timelines may slip. Manufacturing may be harder than expected. Regulatory feedback may change the path. Competitive dynamics may shift. Leadership teams may change. Portfolio priorities may evolve.

The agreement cannot predict everything. It can, however, define how the parties will make decisions when the future arrives.

That may include joint steering committees, workplans, budgets, decision rights, tie-breaking authority, escalation processes, dispute resolution mechanisms, reporting obligations, and amendment processes.

These terms are not administrative clutter.

They determine how the partnership behaves under pressure.

More governance is not automatically better. The goal is decision clarity, escalation discipline, and enough oversight to manage uncertainty without paralyzing the work.

Termination provisions are equally important. They are not pessimism. They are planning for uncertainty.

A thoughtful agreement may address termination for convenience, termination for breach, termination tied to failure to meet criteria, termination after data readouts, post-termination rights, reversion of rights, ongoing obligations, inventory, transition activities, and royalty-back obligations where relevant.

The goal is not to create distrust.

The goal is to create a workable process for decisions that cannot be fully predicted at signing.

For biotech leadership teams, governance and termination provisions deserve executive attention because they shape what happens when the partnership no longer follows the original script.

And no partnership follows the original script perfectly.

Why the Highest Upfront Is Not Always the Best Deal

The highest upfront is not always the best deal.

It may be. But not always.

A high upfront may come with broad exclusivity, expansive field restrictions, limited strategic flexibility, aggressive control provisions, burdensome obligations, unfavorable termination consequences, weak governance protections, or limited ability to pursue adjacent opportunities.

A lower upfront may be acceptable if it preserves meaningful strategic flexibility, funds important work, aligns incentives, includes achievable milestones, creates a path to future value, and gives the company room to continue building.

The point is not that founders should discount upfront economics. They should not. Cash matters. Validation matters. Near-term funding matters.

The point is that upfront economics should be evaluated in context.

A better deal is not always the one with the largest first check.

It is the one that best supports the company’s strategy under realistic future scenarios.

That requires asking harder questions:

What are we giving up?

What are we preserving?

What obligations are we accepting?

What future paths remain open?

What happens if development takes longer?

What happens if the partner deprioritizes the asset?

What happens if the next asset or indication becomes more valuable than the first?

The best deal is not only attractive on signing day. It remains workable when reality becomes more complicated.

What Not to Overinterpret

Deal terms are signals, but they are also tools.

They need to be interpreted in context.

Do not overinterpret:

• a high upfront as the best overall deal

• a low upfront as weak strategic interest

• large total deal value as likely realized value

• broad rights or preserved rights without understanding the full strategy

• detailed governance or termination provisions as mistrust

The question is not whether a term looks favorable in isolation.

The question is how the terms work together.

A deal is an integrated structure. Economics, rights, obligations, governance, manufacturing, IP, and termination all interact.

That is why the same headline economics can support very different business outcomes.

CEO Actions

Before agreeing to a term sheet:

• Evaluate the full deal structure, not only upfront payment and total deal value.

• Define which rights and control points are essential to your company’s future strategy before negotiation begins.

• Understand which obligations, effort standards, manufacturing responsibilities, and governance provisions create real operational or financial burden.

• Pressure-test how the deal behaves if timelines slip, data are mixed, priorities change, manufacturing becomes difficult, or one party wants to exit.

• Align your board, counsel, and advisors on the tradeoffs between economics, control, risk, obligations, and optionality before positions harden.

• Treat the term sheet as the first version of the operating relationship, not just a financial proposal.

Executive Takeaway

The upfront matters, but it is not the whole deal.

Pharma is negotiating more than price. It is negotiating rights, obligations, control, risk allocation, governance, manufacturing responsibilities, IP control, and future optionality.

For biotech leadership teams, the essential question is not only:

How much are they paying?

It is:

What are we agreeing to, what are we preserving, what risks are we allocating, and how will this deal behave if the future changes?

Economics describe value.

Terms determine how value is shared, controlled, protected, and constrained.

One way parties manage uncertainty is through option structures. Option deals can be elegant when both sides agree on the future decision the option is meant to support. They can become problematic when they defer disagreement rather than resolve it.

That is the subject of the next article.

1. After Pharma Says “Interesting”: Why Interest Is Not Yet Momentum

2. The Diligence Readiness Test: What Pharma Needs Before It Can Go Deep

3. Organizing the Evidence: How Data Rooms Support Pharma Decisions

4. Why Two Pharma Companies Value the Same Asset Differently ← You are here

5. Beyond the Upfront: What Pharma Is Really Negotiating

6. Structuring Around Uncertainty: When Options and Collaborations Work

7. Before the First Proposal: The Internal Work Behind Pharma Deal Terms

8. The Deal Is Signed. Now the Partnership Has to Work.

The Same Asset, Two Different Answers

A biotech leadership team may present the same asset to two global pharma companies.

One company leans in.

Another passes.

One sees a strategic opportunity.

Another sees an interesting program that does not rise above competing priorities.

From the outside, this can feel inconsistent. If the data are the same, why are the reactions different?

The answer is that valuation is not only about the asset.

It is about the asset inside a specific company’s strategy, portfolio, capabilities, risk appetite, and alternatives.

This is one of the most important concepts for biotech leadership teams to understand. Pharma companies are not all solving the same problem. They do not have the same portfolios, the same gaps, the same internal capabilities, the same urgency, or the same view of risk.

That does not make valuation arbitrary.

It makes valuation buyer-specific.

Value Is Buyer-Specific

Founders often ask, “What is this asset worth?”

A more useful question is:

To whom is this asset valuable, and what assumptions would make that value actionable?

I use “buyer” here broadly to include a potential acquirer, licensee, or pharma partner evaluating whether, how, and at what level to invest.

In pharma partnering, value is rarely a single number floating in the market. It is a view formed inside a specific strategic and portfolio context.

That view reflects several questions at once:

• What could this asset become?

• How likely is that outcome?

• What would it cost to get there?

• How long would it take?

• How well does it fit the partner’s portfolio?

• What internal capabilities does the company already have?

• What risks remain?

• What alternatives are competing for the same capital, time, and attention?

This is why the same data package can lead to different reactions.

One company may see a path to leadership. Another may see a niche opportunity. A third may see overlap with internal programs. A fourth may see a good asset in an area where it no longer wants to allocate resources.

The asset has not changed.

The buyer has.

What Makes Value Buyer-Specific

The most important valuation questions are not purely financial. They are strategic.

A valuation model can organize the math, but the inputs come from judgment: strategy, risk, differentiation, timing, portfolio context, and confidence in execution.

Several factors make value buyer-specific.

1. Strategic fit

An asset has more value to a company if it reinforces current strategic priorities.

This does not only mean the asset falls within a named therapeutic area. It means the opportunity fits where the company is trying to build leadership, where it is investing capabilities, and where it believes durable value can emerge.

Strategy does not only determine whether an asset is interesting.

It shapes what the organization can justify doing about it.

It also shapes what level of investment the organization can defend internally.

An asset that is squarely aligned with a company’s strategic direction may receive deeper attention, broader internal support, and greater willingness to invest. The same asset may receive a more modest response from a company whose priorities have moved elsewhere.

That is not necessarily a scientific disagreement.

It may be a strategy difference.

2. Portfolio gap or portfolio crowding

A portfolio gap can create urgency.

Portfolio crowding can suppress value.

If a company has a meaningful gap in a therapeutic area, modality, mechanism, stage, or franchise, an external asset may become more valuable because it solves a real portfolio problem.

It may extend a franchise.

It may fill a pipeline gap.

It may create lifecycle optionality.

It may help maintain relevance in a strategically important area.

By contrast, if the company already has internal programs addressing the same biology, indication, or modality, the same asset may be viewed differently. It may be redundant. It may compete for the same resources. It may not be differentiated enough to displace internal investment.

This is why “we like the science” and “we need this asset” are not the same statement.

Scarcity value matters when there are few credible opportunities in a strategically important area. Franchise value matters when an asset strengthens an existing disease-area, platform, or commercial position. Both can make the same asset more valuable to one partner than to another.

3. Internal capabilities

Capability changes perceived risk.

A buyer may value an asset more highly if it already has the capabilities needed to develop, manufacture, regulate, and commercialize it.

That may include:

• disease-area expertise

• modality expertise

• translational tools

• biomarker capabilities

• clinical development experience

• regulatory familiarity

• manufacturing infrastructure

• commercial presence

• market access experience

For one company, a modality may feel unfamiliar or operationally heavy.

For another, the same modality may fit existing infrastructure.

The asset is the same. The execution risk is not.

This is especially important in areas where development, manufacturing, delivery, or commercialization requires specialized capabilities. A company with the right infrastructure may see risk it can manage. A company without that infrastructure may see risk it would need to build around.

That difference can materially affect value.

4. Differentiation and competitive timing

Pharma is not only valuing today’s data.

It is valuing a future competitive position.

An asset may look compelling today but still face a difficult question:

Will this matter when it reaches patients?

That question requires looking beyond the current data package. It requires understanding internal programs, external competitors, standard of care, emerging modalities, regulatory expectations, and market access dynamics.

A buyer may ask:

• Is the asset meaningfully differentiated?

• Is it first-in-class, best-in-class, or otherwise compelling?

• Is the differentiation durable?

• What is likely to reach the market first?

• Could another approach leapfrog it?

• Will physicians, patients, payers, and health systems care about the difference?

Market access belongs in this conversation. A product can be scientifically promising but commercially difficult if the treatment setting, price, reimbursement environment, or adoption pathway is challenging.

The more confident a buyer is that the asset can matter in a future market, the more supportable the value becomes.

5. Risk-adjusted conviction

Potential creates interest.

Risk-adjusted conviction supports value.

This connects directly to the broader theme of this series: pharma is not only asking what the upside could be. It is asking how much uncertainty remains and whether the available evidence supports deeper commitment.

The relevant questions include:

• How much uncertainty has been reduced?

• What risks remain?

• Are the risks understandable?

• Can they be addressed through future studies?

• How much capital and time are required to answer them?

• Can the remaining risk be shared through deal structure?

This is where valuation and diligence meet.

Two potential partners may agree that the upside is large and still disagree on value because they differ in their confidence that the asset can reach that upside.

One may believe the biology is well supported. Another may see translation risk.

One may be comfortable with the modality. Another may see CMC risk.

One may believe the IP position is strong. Another may view exclusivity as fragile.

One may see the clinical path as feasible. Another may see endpoint, biomarker, or trial-design risk.

Same asset. Different conviction.

6. Opportunity cost and internal alternatives

Every valuation is also a comparison.

A pharma company is not asking only whether an asset is good. It is asking whether this asset is the best use of capital, time, expertise, and organizational capacity relative to other choices.

Those choices may include:

• internal programs

• other external assets

• platform investments

• lifecycle investments

• acquisitions

• licensing opportunities

• deprioritizing investment altogether

This matters because resources are finite. Diligence capacity, governance attention, development capacity, and budget are all finite.

An asset may be attractive in isolation and still not clear the internal bar when compared against other opportunities.

That can be frustrating from the outside. From inside the organization, it is central to portfolio management.

A good asset is not always the highest-priority asset.

The Model Is Useful, But the Assumptions Do the Work

Discounted cash flow, or DCF, models and other valuation models can be useful. They allow teams to organize assumptions, compare opportunities, test sensitivities, and understand what drives value.

But a model can create more apparent precision than the underlying assumptions justify.

The model is a tool for organizing assumptions.

The assumptions are where judgment lives.

A valuation model may include patient population, pricing and reimbursement assumptions, adoption curve, market share, development cost, development timeline, probability of success, competitive landscape, IP life, exclusivity, manufacturing cost, royalties, milestones, and deal structure.

Those inputs are not mechanical.

They are debated.

How differentiated is the asset? How confident is the clinical path? How durable is the IP? How large is the addressable population? How difficult will manufacturing be? How much investment is required? How much future competition is expected? How much risk remains?

Good models do not eliminate judgment.

They make judgment visible.

That is why two companies can build models around the same asset and still reach different answers. The visible spreadsheet may look similar. The underlying conviction may be very different.

Valuation Is Not the Same as Deal Structure

Valuation and deal structure are related, but they are not the same thing.

A company may value an opportunity but still resist expressing that value entirely through upfront economics. When risk remains high, value may be expressed through structure rather than immediate price.

That can include:

• development milestones

• commercial milestones

• research funding

• development support

• option structures

• royalties

• field-specific rights

• territory-specific rights

• success-based economics

• co-development or co-commercialization provisions, depending on context

A lower upfront is not always a weaker view of the opportunity. Sometimes it reflects how much uncertainty still needs to be shared, staged, or resolved.

This matters because biotech leadership teams often focus on upfront payment and total deal size. Those are important, but they do not tell the whole story.

The structure of the deal reflects how the parties allocate risk, control, economics, and future optionality.

That is the subject of the next article in this series. But the point here is simple: valuation is not only about what someone believes an asset could be worth. It is also about how much uncertainty remains and how that uncertainty can be handled.

Why Precedent Deals Can Mislead

Precedent deals can be useful reference points.

They can also become misleading anchors.

A public deal headline rarely tells the full story. It may not reveal the true data package, the buyer’s internal portfolio need, the competitive context, the real economics after milestones, the risk-sharing mechanisms, the retained rights, the field or territory limitations, the IP constraints, the diligence findings, the governance provisions, or the strategic urgency at the time.

It also may not reveal what alternatives the buyer was weighing.

This is why a headline number can mislead. It may describe the announced economics, but not the decision logic.

Headline value is not the same as decision value.

For biotech leadership teams, precedent deals should be used carefully. They can help frame a market conversation, but they should not replace buyer-specific analysis.

The better question is not:

What did someone else get?

The better question is:

Why did that buyer value that asset in that context, and what would make my asset valuable to this buyer now?

A Brief Note on Platforms

Platform companies face a related challenge. As I discussed in a prior article on platform versus asset partnering platforms are often easier to value when they are anchored in a product-shaped asset.

A platform may be strategically interesting, but valuation becomes more concrete when there is an asset, indication, development path, and clearer view of risk. The platform may create the possibility; the asset makes value easier to underwrite.

What Not to Overinterpret

Valuation signals matter.

They simply need context.

Do not overinterpret:

• one pharma company’s low valuation as the market’s view

• one pharma company’s pass as a scientific verdict

• a high headline precedent as directly comparable

• a low upfront as lack of strategic interest

• strong scientific interest as agreement on value

Different buyers can reach different views for rational reasons.

That does not mean valuation is arbitrary.

It means valuation is contextual.

CEO Actions

Before entering valuation discussions:

• Identify which pharma companies have the strongest strategic reason to care.

• Understand whether your asset fills a portfolio gap or competes with internal priorities.

• Frame value around buyer-specific fit, not only stage or precedent deals.

• Be explicit about differentiation, durability, IP, manufacturability, and future market relevance.

• Know which assumptions drive your value story and which assumptions are most likely to be challenged.

• Treat valuation as a conversation about risk, conviction, and strategic fit, not only price.

Executive Takeaway

The same asset can have different value to different pharma companies because each buyer is solving a different strategic, portfolio, capability, and risk-allocation problem.

For biotech leadership teams, the question is not simply, “What is this worth?”

The better question is:

Who has the strongest reason to value this, what assumptions would support that value, and what uncertainties still need to be resolved?

Value is not universal.

It is buyer-specific.

Once value is understood as buyer-specific and risk-adjusted, the next question is how that value appears in a deal. Founders often focus on upfront payment and total deal size. Pharma is often negotiating something broader: rights, obligations, control, risk allocation, governance, and future optionality.

That is the subject of the next article.

The data room is where that discipline becomes visible.

For many biotech leadership teams, the data room is treated as a place to upload files: study reports, figures, protocols, IP documents, CMC materials, corporate documents, and anything else that may be requested during diligence.

From the pharma side, it often becomes something more important: the working structure for review.

That distinction matters. Once a broader internal team begins reviewing an opportunity, not everyone has heard the original pitch. Not everyone was in the first scientific discussion. Not everyone understands the company’s internal file history, naming conventions, or assumptions.

The data room becomes the place where the review team encounters the asset on its own.

If the evidence is organized well, review can move more efficiently. If the evidence is difficult to navigate, even strong science can become harder to evaluate.

The goal is not to upload everything.

The goal is to make the evidence usable.

Series: After Pharma Says “Interesting”: How Biotech Partnerships Really Get Made

1. After Pharma Says “Interesting”: Why Interest Is Not Yet Momentum

2. The Diligence Readiness Test: What Pharma Needs Before It Can Go Deep

3. Organizing the Evidence: How Data Rooms Support Pharma Decisions ← You are here

4. Why Two Pharma Companies Value the Same Asset Differently

5. Beyond the Upfront: What Pharma Is Really Negotiating

6. Structuring Around Uncertainty: When Options and Collaborations Work

7. Before the First Proposal: The Internal Work Behind Pharma Deal Terms

8. The Deal Is Signed. Now the Partnership Has to Work.

A Data Room Is Not a Repository

A data room is not just a container. It is a decision-support tool.

A less effective data room says:

Here are the files. Find what you need. The answer is somewhere in there.

A stronger data room says:

Here is the asset. Here is the evidence supporting the thesis. Here are the key risks. Here is what remains unresolved. Here is how the data map to the next decision.

That difference is not cosmetic. It changes how the internal team experiences the opportunity.

Evidence quality and evidence usability are different. A company may have valuable data, but if reviewers cannot understand where the data are, what they support, how they connect, or which questions they answer, the process becomes harder than it needs to be.

In my experience, this matters because diligence is not only a scientific process. It is a cross-functional decision process. The data room should be organized around the questions reviewers need to answer, not simply around the files the company happens to have.

Strong evidence still needs organization.

Evidence Must Survive Cross-Functional Review

The data room has to support more than one reader.

A scientific founder may think of the data room as a scientific archive. A pharma organization may experience it as a cross-functional review environment. Those are not the same thing.

Depending on the opportunity and stage of review, the data room may be used by external innovation or search and evaluation teams, biology and pharmacology experts, translational scientists, DMPK and PK/PD reviewers, toxicologists, CMC and manufacturing specialists, IP counsel, clinical development leaders, regulatory colleagues, commercial and market access teams, finance, legal, and business development.

Each function is not reading for the same answer.

Biology reviewers may ask whether the mechanism makes sense. Translational scientists may ask whether the biology can move toward humans. DMPK reviewers may ask whether exposure can support the biology. Safety reviewers may look for emerging risks. CMC reviewers may ask whether the product can be made, controlled, and scaled. IP counsel may ask whether value can be protected. Clinical development may ask what path is plausible. Commercial colleagues may ask whether the product can matter in a future market. Finance may ask what assumptions drive value. Legal and BD may ask what rights, risks, obligations, and structures could matter.

This is why a data room organized only as a historical archive can become frustrating.

The diligence team is not trying to reconstruct the company’s past. It is trying to understand whether the evidence supports a future decision.

What Good Data Room Organization Looks Like

A strong data room is organized around decision logic, not file accumulation.

It should help the review team move from question to evidence to implication.

The exact structure will depend on the asset, modality, stage, indication, and nature of the partnering discussion. A preclinical small molecule, an antibody, a genetic medicine, a cell therapy, a platform-derived asset, and a Phase 2-ready program will not require identical review.

Still, several principles apply broadly.

1. Orientation layer

The first layer should orient the reviewer before they begin navigating the supporting materials.

This does not need to be long. In fact, it should not be. It should help reviewers quickly understand what they are looking at.

Depending on stage, this may include:

• a short asset overview

• current development stage

• indication and patient population

• mechanism and modality

• key data summary

• key risks and open questions

• current ask or diligence objective

This layer is especially useful because many reviewers will enter the data room without the full context of the first meeting. The orientation layer helps the story survive translation.

2. Evidence by workstream

Organize evidence by how the opportunity will be reviewed, not by how files happened to accumulate internally.

For example, workstreams might include:

• biology / pharmacology

• translational / biomarkers

• DMPK / PK-PD

• toxicology / safety

• CMC / manufacturing / quality

• clinical / regulatory

• IP

• commercial / competitive

• finance / corporate

• legal / contracts, where relevant

The point is not to create unnecessary complexity. The point is to help each reviewer find the evidence relevant to their question.

3. Decision-relevant summaries

Each major workstream should include a short summary.

The summary should explain what was done, what was shown, what the evidence supports, what remains uncertain, and where the underlying source documents can be found.

Summaries do not replace source documents. They help reviewers navigate them.

This distinction is important. A summary without source documents can feel promotional. Source documents without summaries can feel like an excavation site. The strongest data rooms provide both: a clear path through the evidence and the underlying materials needed to verify it.

4. Clear source documents

The underlying evidence should be traceable.

Depending on stage and relevance, source documents may include final study reports, protocols, methods, raw, processed, or summarized datasets where appropriate, assay validation materials, manufacturing records, IP documents, regulatory correspondence where appropriate, financial or corporate documents when appropriate, and other materials needed to support review.

Not every item is required for every opportunity.

The principle is simpler: reviewers should be able to trace important claims back to credible source material.

5. Risk and gap register

One of the most useful tools a company can provide is a risk and gap register.

This does not need to be elaborate. It should identify known gaps, open questions, planned studies, expected timing, decision impact, and the owner or workstream responsible for follow-up.

A gap that is named and managed is different from a gap that reviewers have to discover themselves.

This is not about volunteering weakness in a naïve way. It is about showing that the leadership team understands the remaining uncertainty and has a plan for addressing it.

That builds confidence.

Not because the gaps disappear, but because the company is demonstrating disciplined thinking about them.

6. Access discipline and version control

Access discipline is not only about confidentiality. It is also about maintaining an orderly review.

As review deepens, staged access, permissioning, printing or downloading restrictions where appropriate, document version control, question logs, update logs, and a clear point of contact can all help keep the process organized.

This should not become performative. Overly complex controls can slow review and frustrate the diligence team.

But thoughtful access management signals that the company understands the balance between transparency, confidentiality, and review needs.

A Simple Example: File Storage vs. Decision Support

A less effective data room might be organized around the company’s internal file history: old folders, inconsistent labels, multiple versions, and no clear path through the evidence.

A stronger data room is organized around how the opportunity will be reviewed: asset overview, key data summaries, source documents, risk and gap register, IP, CMC, clinical and regulatory materials, commercial context, and corporate materials as appropriate.

The difference is not the number of files.

The difference is whether the evidence has been organized for someone else’s decision process.

This is where many leadership teams can improve quickly. The company may already have the information. What may be missing is the structure that allows another organization to understand it.

Transparency Does Not Mean Everything Belongs in the Room on Day One

A well-organized data room should support transparency.

But transparency does not mean every piece of sensitive information belongs in the room on day one.

Depending on the stage of discussion, certain information may need to be staged, redacted, discussed live, or held until the right confidentiality and review conditions are in place. For example, the structure of a small molecule, certain trade secrets, or highly sensitive know-how may require more deliberate handling.

The point is not to withhold information in a way that impairs review.

The point is to balance transparency, confidentiality, and decision need.

This is one reason data-room strategy requires judgment. Too little information prevents serious review. Too much sensitive information too early can create avoidable risk. The best approach is neither reflexive disclosure nor reflexive protection. It is disciplined information management.

Why More Data Can Create Less Confidence

A large data room can feel reassuring to the company that built it.

To the reviewer, volume without organization can create fog.

More data can create less confidence when the most important evidence is hard to find, duplicate or outdated versions create confusion, summaries do not match underlying reports, key studies lack context, or gaps are buried rather than framed.

In those situations, the diligence team spends time navigating rather than evaluating.

A disorganized data room may not decide the outcome, but it can create friction and affect how prepared the company appears.

That matters because diligence is not only about the asset. It is also about whether the company can support a serious process.

When the data room is difficult to use, the company may unintentionally signal fragmentation, lack of internal alignment, or immaturity in partner readiness.

That may not be the reality.

But in diligence, the way evidence is presented can shape how the organization is perceived.

The Data Room Is Also a Behavioral Signal

Pharma is not only reviewing the asset.

It is also learning how the company behaves under scrutiny.

A strong data room can signal preparation, transparency, discipline, respect for reviewer time, awareness of uncertainty, and readiness for partnership.

A poorly organized data room can signal fragmentation, overpromotion, lack of internal alignment, avoidance of difficult questions, or inability to support diligence at scale.

This does not mean a messy data room kills an opportunity. Strong science still matters. Strategic fit still matters. Differentiation still matters.

But friction matters too.

If the review is harder than it needs to be, internal momentum can slow. Questions take longer to answer. Reviewers may become less confident that they are seeing the full picture. Internal advocates may have a harder time carrying the opportunity forward.

A good data room does not make a weak asset strong.

It makes a strong asset easier to evaluate.

What Not to Overinterpret

The purpose of a data room is not to eliminate questions.

It is to make better questions possible.

Do not overinterpret:

• a large data room as a strong data room

• a clean data room as a substitute for strong evidence

• staged access as lack of transparency

• many reviewer questions as evidence that the data room failed

• a request for missing materials as a negative signal

A good data room should invite serious questions. That is part of the point.

The goal is not silence.

The goal is better review.

CEO Actions

Before opening a data room:

• Create a short orientation layer that explains the asset, thesis, key evidence, risks, and open questions.

• Organize evidence by diligence workstream, not by historical file storage.

• Include decision-relevant summaries that point reviewers to the underlying source documents.

• Maintain a risk and gap register that names open questions and planned work.

• Use staged access, version control, and a question log to manage review discipline.

• Assign one owner for data-room quality, updates, permissions, and follow-up.

Executive Takeaway

A data room is not a repository. It is a decision-support tool for serious internal review.

The strongest data rooms help reviewers understand the asset, locate the evidence, assess the risks, and see what decision the data can support. They do not replace strong science. They make strong science easier to evaluate.

For biotech leadership teams, the goal is not to upload everything. The goal is to organize evidence so another organization can make sense of it.

Strong evidence still needs organization.

Once evidence is organized well enough for serious review, the next question is value. But value is not universal. The same asset can look different to different pharma companies depending on strategy, portfolio context, internal capabilities, competitive urgency, and risk appetite.

That is the subject of the next article.

Author’s Note: In the first article in this series, I wrote that a positive pharma meeting is not the same as momentum. Momentum begins when scientific interest becomes a defined internal next step.

Often, that next step is some form of deeper review.

This is where many biotech leadership teams begin to experience the process as diligence.

But diligence is often misunderstood. It is not simply a request for documents, a search for weaknesses, or a ceremonial step toward a deal.

It is a structured process for determining whether the asset, the company, and the opportunity can support a serious internal decision.

That distinction matters because diligence is where the conversation changes. The question is no longer only whether the science is interesting. The question becomes whether the evidence can withstand deeper review and support the next decision.

That is a different standard.

Series: After Pharma Says “Interesting”: How Biotech Partnerships Really Get Made

1. After Pharma Says “Interesting”: Why Interest Is Not Yet Momentum

2. The Diligence Readiness Test: What Pharma Needs Before It Can Go Deep ← You are here

3. Organizing the Evidence: How Data Rooms Support Pharma Decisions

4. Why Two Pharma Companies Value the Same Asset Differently

5. Beyond the Upfront: What Pharma Is Really Negotiating

6. Structuring Around Uncertainty: When Options and Collaborations Work

7. Before the First Proposal: The Internal Work Behind Pharma Deal Terms

8. The Deal Is Signed. Now the Partnership Has to Work.

Diligence Is Not an Exam

Diligence can feel like an exam because the questions are detailed and the stakes are high.

The scientific team may ask for additional data. CMC reviewers may ask about manufacturability. IP counsel may ask about patent position, prosecution strategy, freedom to operate, or know-how. Clinical, regulatory, and commercial colleagues may begin asking questions that feel early for a preclinical company.

From the biotech side, this can feel like a sudden expansion of scrutiny.

From inside pharma, the purpose is not to find imperfection. Early-stage programs are imperfect by definition.

The purpose is to understand what is known, what remains uncertain, what risks matter most, and whether the available evidence supports the next decision.

This is why diligence readiness is different from having a complete answer to every question. At early stages, no company has every answer. What matters is whether the leadership team can explain the current state of the evidence with clarity.

The relevant questions are: what do the data show, what do they not yet show, which risks are material, what additional work would reduce uncertainty, and what decision can be supported now?

Diligence is not an exam to pass. It is a decision process to support.

Diligence Requires Translation

Diligence is not only about what the data show. It is about whether the company can help another organization understand the evidence, the risks, and the decision the data can support.

That is the part many leadership teams underestimate.

A company is not only providing reports, figures, files, and answers. It is helping a cross-functional organization interpret what the evidence means.

That requires communication discipline: relevant information, prepared participants, clear ownership, access to the right specialists, disciplined responses, honest risk framing, and a shared understanding of the question being answered.

Diligence converts information into confidence, or reveals why confidence cannot yet be built.

That does not make diligence adversarial. Done well, it is a structured conversation. It allows both sides to understand whether the opportunity is ready for deeper investment of time, attention, and resources.

What Pharma Needs Before It Can Go Deep

Before pharma can go deep, it needs more than interest. It needs enough clarity to justify deeper internal effort.

A useful way to think about diligence readiness is through five dimensions.

1. A clear asset narrative

The leadership team needs a concise explanation of what the asset is, what problem it is solving, why the biology matters, and why the approach is differentiated.

This is not a marketing story. It is a decision story.

The narrative should help internal reviewers understand the mechanism, target indication, evidence supporting the biology, basis for differentiation, development path, and key uncertainties.

It should also be disciplined enough that it can be repeated internally without losing meaning. That matters because the person who first met the company may not be the person evaluating CMC, IP, clinical development, regulatory path, commercial opportunity, or valuation.

The story has to survive translation.

2. Decision-relevant data

Not every experiment carries the same weight.

Diligence does not ask one question. It asks whether the asset can survive a chain of questions.

For an early-stage program, decision-relevant data may span several domains. The categories matter less as a checklist than as a reminder that diligence is cross-functional.

• Biology and mechanism: target rationale, disease relevance, mechanism of action, and evidence that the biology is meaningfully connected to human disease.

• Pharmacology and translation: potency, specificity, target engagement, dose-response, durability, relevant disease models, biomarkers, and evidence that preclinical findings can plausibly translate.

• PK/PD, DMPK, and safety: exposure, distribution, clearance, exposure-response, therapeutic window, early tolerability, off-target risks, and modality-specific safety concerns.

• CMC and manufacturability: whether the product can plausibly be made, characterized, formulated, scaled, controlled, and released with appropriate quality.

• Clinical and regulatory path: proposed indication, patient population, biomarker strategy, endpoint logic, clinical feasibility, regulatory precedent, and major development questions.

• IP, competitive, and commercial position: patent protection, freedom to operate, know-how, differentiation versus internal and external alternatives, unmet need, treatment setting, market access considerations, and long-term relevance.

• Operational readiness: quality of records, study reports, protocols, assay reliability, reproducibility, data provenance, and whether the company can answer questions consistently.

The exact mix depends on the asset, modality, stage, indication, and partnering question. A preclinical small molecule, an antibody, a genetic medicine, a cell therapy, a platform-derived asset, and a Phase 2-ready program will not all be reviewed in the same way.

The key is not to overwhelm reviewers with every available figure.

The key is to help them understand which data matter most and why.

A leadership team should be able to say:

These are the data that support the core thesis. These are the data that reduce the most important uncertainties. These are the questions that remain.

That is far more useful than a large, unstructured data package.

3. Transparent risk framing

Strong diligence does not require pretending the risks are gone.

It requires understanding them.

In my experience, the best biotech leadership teams do not hide uncertainty. They frame it. They can explain what is known, what is unknown, what matters most, and what future data would change the level of confidence.

That matters because pharma teams are not only evaluating upside. They are evaluating whether risk is understandable, manageable, and worth taking relative to other opportunities.

A vague risk is hard to support.

A clearly framed risk can be discussed, tested, priced, structured, or deferred to a future milestone.

4. Access to the right specialists

Diligence often expands beyond the original conversation.

That is not a bad sign. It is often how deeper review works.

As review advances, pharma may need access to people who can speak credibly about biology, pharmacology, translational science, DMPK, PK/PD, toxicology, CMC, IP, clinical development, regulatory strategy, or commercial assumptions.

The key is not to bring every specialist into every meeting. That can overwhelm the process.

The key is to know who should answer which questions and to make those people available when needed.

Specialist access matters because diligence is not only about the CEO’s ability to tell the story. It is about whether the organization can support the story under scrutiny.

5. Internal discipline

Diligence can become chaotic if information flow is not managed.

A biotech company should have a clear point of contact, consistent messaging, and an internal process for responding to questions. The team should know who owns which workstream, which materials have been shared, which questions remain open, and which answers require follow-up.

This sounds administrative.

It is not.

Internal discipline affects confidence.

If the story changes depending on who answers, if materials arrive inconsistently, if key files are hard to locate, or if different team members frame the risks differently, the process can lose energy.

Not because the science necessarily failed.

Because the review became harder to complete.

Why Strong Science Can Still Struggle in Diligence

Strong science is necessary.

It is not always sufficient.

Diligence can stall when the evidence is difficult to evaluate, even if the underlying science is promising.

That can happen when the data package is fragmented, the story changes depending on who is speaking, key experts are unavailable, gaps are minimized rather than framed, or materials are too large, too sparse, or difficult to interpret.

It can also happen when a company treats certain questions as “later” when they are already relevant.

CMC may feel like a later problem. IP may feel like a legal problem. Commercial positioning may feel premature. Regulatory path may feel distant.

But these questions can influence whether the asset can become a drug, whether it can be protected, whether it can be manufactured, whether it can be developed, and whether it can matter in a future market.

This does not mean every answer must be complete.

It means the leadership team should be able to show that it understands the path ahead.

In many cases, diligence stalls less because a company lacks every answer, and more because the answers are difficult to evaluate.

The job of the biotech leadership team is not to eliminate all uncertainty.

It is to make uncertainty legible.

What Not to Overinterpret

Diligence is a meaningful step.

It means the opportunity has earned deeper attention.

But deeper attention is still not the same as commitment.

Do not overinterpret:

• a diligence request as evidence that a deal is likely

• many questions as negative interest

• difficult questions as hostility

• a CDA as a substitute for internal conviction

• a pause during diligence as a final answer

Signals matter, but diligence signals need context.

Many questions can mean the team is engaged. Difficult questions can mean reviewers are doing their work. A pause can mean the internal team is coordinating across functions, waiting for expert input, or deciding whether the next level of review is justified.

At the same time, diligence can reveal issues that reduce confidence.

Both can be true.

Diligence is not a promise.

It is a process for deciding whether a promise is supportable.

CEO Actions

Before deeper review begins:

• Align internally on the asset narrative, key data, open risks, and development path.

• Identify the specialists who can answer scientific, translational, technical, IP, CMC, clinical, regulatory, and commercial questions.

• Prepare to explain not only what the data show, but what decision the data support.

• Be explicit about known gaps and the studies or milestones that could address them.

• Establish a single point of contact and a disciplined process for information flow.

• Treat diligence as a trust-building process, not a defensive exercise.

Executive Takeaway

Diligence is not simply a request for information.

It is the process by which pharma determines whether an opportunity can support a serious internal decision.

The strongest biotech leadership teams do not treat diligence as an exam to survive. They treat it as a disciplined communication process: clarify the evidence, frame the risks, provide access to the right experts, and help the internal team understand what decision the data can support.

Diligence converts information into confidence, or reveals why confidence cannot yet be built.

Once a company is ready for deeper review, the next question is whether the evidence is organized in a way that supports decision-making. That is where the data room becomes more than a repository. It becomes the architecture through which reviewers understand the asset, the risks, and the path forward.

That is the subject of the next article.

This series begins one step later.

What happens after pharma says, “This is interesting”?

For many biotech leadership teams, this is where the process becomes most difficult to read. A meeting goes well, questions are thoughtful, and the tone is constructive. Then the pace changes. More stakeholders appear. Diligence requests expand. Valuation assumptions diverge. Deal terms introduce new complexity.

From the outside, this can feel opaque.

From the inside, it is a structured process for determining whether scientific interest can become institutional commitment.

This series explains how global pharma converts initial scientific interest into diligence, valuation, deal architecture, negotiation, and post-signature execution.

This series reflects a general perspective on biotech-pharma partnering. It is not legal, financial, investment, or company-specific advice.

Series: After Pharma Says “Interesting”: How Biotech Partnerships Really Get Made

1. After Pharma Says “Interesting”: Why Interest Is Not Yet Momentum ← You are here

2. The Diligence Readiness Test: What Pharma Needs Before It Can Go Deep

3. Organizing the Evidence: How Data Rooms Support Pharma Decisions

4. Why Two Pharma Companies Value the Same Asset Differently

5. Beyond the Upfront: What Pharma Is Really Negotiating

6. Structuring Around Uncertainty: When Options and Collaborations Work

7. Before the First Proposal: The Internal Work Behind Pharma Deal Terms

8. The Deal Is Signed. Now the Partnership Has to Work.

The Meeting Went Well. Now What?

The meeting went well.

The pharma team understood the science. The questions were thoughtful. The tone was constructive. There may even have been language that sounded encouraging: “This is interesting,” “We would like to understand more,” or “Let us discuss internally.”

Then the pace changes.

A follow-up may take longer than expected. More people may appear. A request for additional information may arrive. Or the conversation may become quieter, even though nothing negative was said.

For many biotech leadership teams, this is where the process becomes hardest to interpret. The leadership team is left to interpret the signal: whether the opportunity is advancing, whether diligence has begun, or whether silence should be read as rejection.

The answer is often more nuanced.

A positive meeting can be genuine and still not yet represent momentum.

That distinction matters.

Interest Is Not Yet Momentum

Inside a large pharmaceutical organization, “interesting” is not a decision. It is not a commitment. It is not yet internal alignment.

It is the point where scientific interest has to be translated into the next internal question.

Who needs to evaluate this? What uncertainty needs to be resolved? What information is missing? What would justify deeper review? Is there a clear next step, or only general curiosity?

A positive meeting matters. It means the opportunity earned attention. But attention is not yet momentum.

Momentum begins when scientific interest becomes a defined internal next step.

In my experience, this is where many external conversations either advance or quietly lose energy. Not necessarily because the science is weak. Not because the meeting was insincere. But because interest must be converted into something the organization can act on.

No large organization can apply full diligence, valuation, legal, and governance resources to every interesting opportunity. It has to decide which opportunities merit deeper internal effort.

That decision is not made from enthusiasm alone. It depends on whether the opportunity can be translated into a decision-relevant question.

What Happens Inside Pharma After the Meeting

A constructive external meeting creates internal work.

The opportunity has to be translated for the organization. Depending on the opportunity and the stage of the conversation, that translation may involve scientific experts, clinical development leaders, commercial colleagues, IP counsel, CMC specialists, finance, legal, external innovation, and business development.

The question is not simply whether someone liked the meeting.

The question is whether enough conviction exists to justify the next layer of review.

After a positive discussion, the internal team may need to identify the right stakeholders, determine whether the opportunity is aligned with current priorities, clarify key uncertainties, decide whether confidential information is needed, and agree on what the next interaction should accomplish.

This is why the business and scientific tracks matter at the same time.

On the business side, teams may need to assess interest, identify a primary point of contact, determine whether a CDA, or Confidential Disclosure Agreement, is appropriate, agree on next steps, and manage information transfer. On the scientific side, teams may need to identify the right technical stakeholders, consider whether an MTA or feasibility study is relevant, and keep technical achievability aligned with strategic intent. This reflects the broader partnering process: non-confidential exchange, CDA, communication of interests and issues, joint planning, diligence, term sheet, and contract.

That process is not perfectly linear. Real life is messier than a slide deck. But the underlying point is important: interest has to enter an operating system.

It has to become ownership, next steps, information flow, and internal discussion.

Without that translation, an opportunity can remain interesting but inactive.

Why Momentum Can Feel Slow Even When Interest Is Real

Silence after a constructive meeting does not always mean rejection.

It can mean the organization has not yet determined whether the opportunity should move from interest to alignment.

From the outside, this can feel like drift. From the inside, it may reflect a sorting process: who should review the opportunity, what question needs to be answered, what information is needed, and whether the opportunity can compete for deeper attention inside a crowded portfolio.

This is where the distinction between interest and alignment becomes important.

In a prior article, I distinguished interest from alignment. Interest means the opportunity is worth further discussion. Alignment means the organization sees a reason to allocate additional attention and resources.

This article focuses on the space between those two states.

That space can be uncomfortable for biotech leadership teams because it is rarely visible. Initial enthusiasm has to survive internal skepticism. The opportunity may need to be routed to the right experts. Business and scientific stakeholders may not yet have formed a shared view. A CDA may be needed before deeper review can proceed. Key technical questions may need to be clarified. Internal programs or other external opportunities may be competing for attention.

Sometimes, the next step is unclear because the question has not been made clear enough.

This is not an argument that pharma communication is always as clear as it should be. Ambiguity can be frustrating, and well-run processes benefit from disciplined follow-up on both sides.

But a pause does not always mean the same thing.

Sometimes the opportunity is losing priority.

Sometimes the right internal owner has not yet emerged.

Sometimes the team is waiting for a specific data update.

Sometimes the opportunity is interesting, but not yet actionable.

And sometimes the leadership team can help by making the next decision easier to define.

What Biotech Leadership Teams Can Do After a Positive Meeting

The strongest follow-up does not simply say, “Thank you for the meeting.”

It helps the internal team do its work.

A more useful follow-up asks:

“Based on our discussion, what question would your team need answered to determine whether broader internal review is warranted?”

After a constructive pharma meeting, biotech leadership teams can improve the quality of follow-up by clarifying what was discussed, what data are available, what uncertainty remains, and what specific question the next interaction should answer.

This does not require over-selling. In fact, over-selling or attempting to create FOMO can create friction. What helps most is precision.

A useful follow-up might clarify the asset, mechanism, indication, data package, differentiation, development path, and open questions. It might identify which materials can be shared internally. It might offer access to the right scientific or technical specialists. It might ask what information would be most useful for the next internal discussion.

The goal is not to force momentum.

The goal is to make the next decision easier to define.

That distinction matters because global pharma organizations do not move opportunities forward simply because a meeting was positive. They move opportunities forward when the next step has a purpose.

Is the next step a scientific follow-up? A CDA? Diligence preparation? An MTA or feasibility discussion? A request for additional data? A decision to pause until a future inflection point?

Clarity on that question helps both sides.

It also signals executive maturity. Leadership teams that understand the decision process are easier to work with. They do not simply ask, “Are you interested?” They help define what interest would need to become.

What Not to Overinterpret

Signals matter. They simply need to be interpreted in context.

A positive tone matters. It means the conversation was constructive.

Thoughtful questions matter. They show engagement.

A CDA may matter. It can indicate that the opportunity has earned deeper review.

Additional stakeholders may matter. They may mean the conversation is broadening.

But none of these signals, alone, means that internal momentum has been established.

In my experience, the stronger question is not, “Was the signal positive?”

The stronger question is, “What decision does this signal support?”

Do not overinterpret:

• a positive tone as internal alignment

• thoughtful questions as a transaction signal

• a CDA as evidence that a deal is likely

• additional stakeholders as automatic escalation

• silence or slowness as lack of interest

A positive meeting earns attention. Momentum begins when that attention becomes a defined internal next step.

CEO Actions

After a constructive pharma meeting:

• Prepare a concise, forwardable summary that connects the asset, data, differentiation, and development path.

• Ask what specific question would need to be resolved to justify deeper internal review.

• Clarify the next step: scientific follow-up, CDA, diligence preparation, MTA or feasibility discussion, future data update, or no current action.

• Make the right specialists available without overwhelming the process.

• Follow up with progress, not pressure.

• Treat every interaction as part of the internal case being built for or against further engagement.

Executive Takeaway

Initial interest is valuable, but it is not the same as momentum.

Momentum begins when scientific interest is translated into a clear internal next step, with the right stakeholders, the right information, and a decision-relevant question to answer.

For biotech leadership teams, this changes the goal after a positive meeting. The goal is not to interpret tone, chase urgency, or assume that interest will carry itself forward.

The goal is to help convert interest into the next decision.

Once interest becomes a defined next step, the next question is whether the company is ready to support deeper review. That is where diligence begins, not as a document request, but as a disciplined process for determining whether the asset and the organization can support a serious partnering decision.

That is the subject of the next article.

BIO 2026 is June 22–25 at the San Diego Convention Center. For therapeutics startups seeking strategic engagement with global pharma, BIO is not simply a networking event. It is a concentrated triage environment.

For attendees using BIO Partnering through the appropriate registration package, the system enables companies to search for potential partners, send and respond to meeting requests, and schedule meetings around mutual availability.

That matters because pharma teams may be interested in the science, but they are also sorting opportunities by strategic relevance, scientific credibility, and whether a follow-up discussion is worth internal time.

In large pharma, attention is a scarce resource. A strong BIO meeting helps the company decide whether the opportunity deserves more of that resource after the conference.

The goal is not to fill your calendar.

The goal is to build a useful calendar.

A useful calendar also requires discipline. Not every accepted meeting is equally valuable, and not every inbound request deserves the same attention. A few high-quality meetings with strategically relevant companies are more valuable than a crowded schedule of superficial conversations.

Not every point below applies equally to every company. A discovery-stage platform, a preclinical asset company, and a clinical-stage therapeutics company will prepare differently. But the underlying principle is the same: make the opportunity easier to understand, route, and evaluate.

1. Know whether you are ready to be visible

For startups still operating partly in stealth, the first question is whether visibility now creates value.

In When Should a Biotech Exit Stealth?, I wrote that exiting stealth is not about visibility for its own sake. It is about readiness for engagement. The real tradeoff is not risk versus safety, but isolation versus momentum.

At BIO, excessive opacity can create a practical problem. If your profile, meeting request, website, or non-confidential deck does not clearly explain what you are building, pharma may not have enough information to prioritize the meeting.

Stealth can protect value.

But at a partnering conference, insufficient clarity can prevent evaluation.

2. Target companies where your asset is plausibly on strategy

The strongest BIO preparation begins before the meeting request.

In When Should Biotech CEOs Engage Global Pharma?, I wrote that strategy is the first filter. Before science is debated, pharma asks whether the opportunity is on strategy right now.

That principle becomes even more important at BIO. Pharma teams are reviewing many requests quickly. A generic meeting request is easy to decline. A targeted request that connects your asset to a company’s therapeutic area, modality interest, portfolio direction, or stated strategic priority is easier to route internally.

Do not ask only:

Would this pharma company be interested in innovation?

Ask:

Why would this specific pharma company care about this specific asset now?

That is a more disciplined question, and it leads to better meetings.

3. Be explicit about the conversation you are seeking

Once you have identified companies where your asset is plausibly on strategy, define the purpose of the conversation.

Are you seeking strategic feedback? A first non-confidential discussion? CDA-enabled diligence? A research collaboration? An option-based structure? Investment? Licensing dialogue? A longer-term strategic relationship?

This does not mean forcing the conversation prematurely. It means making the purpose legible.

In Execution: Timing and Tactics of Engaging Pharma, I emphasized that effective outreach explicitly connects the program to stated strategy, summarizes key data, includes forwardable materials, and requests a focused introductory discussion.

A clear ask signals maturity. A vague request for “partnership” forces the recipient to guess what kind of discussion you actually want.

4. Make sure your materials match the confidentiality level

For BIO, do not bring one undifferentiated deck to every conversation.

At minimum, have a concise non-confidential deck that can circulate internally. Know what can be discussed without a CDA. Know what should wait until a confidential discussion.

This connects directly to Partnering Conferences: What Works and What Doesn’t When Engaging Pharma, where I wrote that registrant metadata and non-confidential decks matter because they help pharma determine whether a meeting is likely to change conviction.

If materials cannot be understood, forwarded, or internally discussed, momentum stalls.

5. Make your public footprint consistent with your partnering story

Your partnering profile, website, non-confidential deck, recent press releases, and LinkedIn presence should tell the same story because each may be used by different internal stakeholders to understand and route the opportunity.

For pharma, inconsistency creates friction. If your meeting request says one thing, your deck says another, and your website emphasizes something else, the opportunity becomes harder to understand and harder to route.

Clarity is not cosmetic.

It is part of strategic readiness.

6. Bring data that reduces uncertainty

In How Much Data Is Enough?, I wrote that being on strategy does not guarantee engagement. It opens the door to evaluation. Data sustains that evaluation.

At BIO, the most useful data are not always the newest data. They are the data that answer the next internal question.

For therapeutics startups, this may include evidence of target engagement, relevant in vivo efficacy, potency, specificity, translational rationale, biomarker logic, emerging PK/PD, CMC feasibility, or differentiation versus the competitive landscape.

The strongest meetings help pharma answer:

Is this worth deeper internal review?

The question is not only whether the science is promising, but whether the opportunity is internally defensible enough to justify the next layer of review.

That is different from asking whether the science is interesting. Interesting science creates attention. Reduced uncertainty creates follow-up.

7. If you are a platform company, show the asset

Platform companies should be especially disciplined at BIO.

In Platform vs Asset: Why Pharma Almost Always Chooses the Asset, I wrote that pharma evaluates drugs more naturally than platforms because drugs have mechanisms, indications, development paths, risks, and potential target product profiles. Platforms become more actionable when they produce evaluable outputs.

So do not only describe the engine.

Show what the engine has produced.

A platform pitch becomes stronger when it includes a lead asset, differentiated molecules, validated outputs, or evidence that the platform can generate better product candidates than existing approaches.

8. Do not confuse urgency with conviction

Large partnering conferences can create pressure to signal momentum. Founders may be tempted to emphasize how many companies are interested, how quickly the process is moving, or how competitive the opportunity has become.

In Why Creating FOMO Does Not Work in Pharma Partnering, I wrote that pharma decisions are not driven by urgency. They are driven by conviction.

That matters at BIO.

The best signal is not:

Many groups are looking at this.

The better signal is:

We have generated data that addresses an important uncertainty.

Progress creates momentum. Pressure creates friction.

Put differently, the best BIO meetings do not create a decision on the spot. They create the conditions for internal advocacy to begin.

In Inside Pharma: How Advocacy Actually Works, I wrote that advocacy is the internal process through which an opportunity gains support, alignment, and conviction over time. It is built through repeated interactions, increasing data, and progressive resolution of uncertainty.

A short BIO readiness check

Before sending or accepting meetings, therapeutics startups should ask:

1. Is this company strategically relevant to our asset, modality, indication, or platform output?

2. Can we explain why this specific pharma company might care now?

3. Can the recipient understand our opportunity from the profile and short request alone?

4. Are we clear on the type of conversation we are seeking?

5. Are our website, profile, and non-confidential deck consistent?

6. Do we know what we can discuss without a CDA?

7. Are we optimizing for a useful calendar, not just a full one?

BIO will generate thousands of conversations.

Most will fade quickly.

The meetings that matter are the ones that leave pharma with a clear internal question worth pursuing:

Should we take a closer look?

That is the standard to prepare for: not persuasion in the room, but enough clarity and conviction to justify the next internal decision.

• pharma evaluates opportunities through uncertainty reduction

• decisions are driven by data

• internal advocacy builds through increasing conviction
  

Against that backdrop, one behavior from biotechs I often encounter is the attempt to create urgency—what is often referred to as FOMO.

This is part of a series on how pharma actually makes decisions.

Series Navigation:

1. What Pharma Is Actually Evaluating When You Ask for a Partnership

2. Why Most Academic Discoveries Do Not Become Partnerships

3. Inside Pharma: How Advocacy Actually Works

4. Partnership Structures Are Not What You Think They Are

5. Platform vs Asset: Why Pharma Almost Always Chooses the Asset

6. Why Creating FOMO Does Not Work in Pharma Partnering ← You are here
   

A Common Misconception

A misconception I often encounter is that signaling external interest will accelerate engagement with pharma.

This can take different forms:

• “For transparency, we are speaking with several other pharma companies”

• “We are already under CDA with multiple groups”

• “We expect to move quickly”
  

The intent behind this is understandable.

From the outside, it can seem like:

• increased competition should accelerate decision-making

• urgency should create momentum

• signaling demand should increase interest

Why This Approach Does Not Work

Inside pharma, this framing does not have the intended effect.

Because:

decisions are not driven by urgency
they are driven by conviction

Conviction is built through:

• data

• evaluation

• internal alignment
  

None of which can be meaningfully accelerated by signaling that others are interested.

Pharma Does Not Optimize for Speed

Another important point:

Pharma is typically not optimizing to be first to negotiate.

It is optimizing to be right.

Which means:

• taking the time to evaluate properly

• ensuring internal alignment

• understanding the risk profile of the asset
  

Moving too quickly increases the probability of being wrong.

That is not a tradeoff we are willing to make.

Internal Processes Reflect the Complexity of the Decision

Even when an asset is promising, internal processes still require:

• scientific evaluation

• internal discussion

• cross-functional input

• prioritization relative to other opportunities
  

These steps are not procedural overhead.

They reflect the reality that:

this is a complex decision with long-term consequences

Reaching Out to Senior Leadership

Another related misconception is that escalating outreach to senior leadership will accelerate the process.

For example:

• reaching out directly to the CEO

• contacting the head of R&D

• attempting to create visibility at the highest levels
  

In practice:

this does not change the evaluation pathway

Opportunities are routed back to the teams responsible for:

• search and evaluation

• external innovation

• disease area expertise
  

Senior leaders rely on these teams to assess opportunities.

So the result is typically:

the same process—just entered from a different angle

What Actually Moves a Decision Forward

If urgency does not move decisions, what does?

The answer is consistent across this series:

data that reduces uncertainty

More specifically:

• new data that addresses previously identified gaps

• new data that increases PTRS

• new data that changes internal conviction
  

This ties directly to:

• What Pharma Is Actually Evaluating When You Ask For a Partnership

• Inside Pharma: How Advocacy Actually Works

• From Interest to Alignment
  

Without movement along this dimension:

time alone does not change the outcome

A More Effective Signal: Progress

The most effective way to create momentum is not to signal urgency, but to demonstrate progress.

For example:

• “Since our last discussion, we have generated data demonstrating…”

• “We have addressed the PK/PD question that was raised…”

• “We now have evidence of target engagement in vivo…”
  

This does two things:

1. It shows responsiveness

2. It directly contributes to uncertainty reduction
   

Which is what actually drives decisions.

A Subtle but Important Distinction

It is not that pharma is unaware of external dynamics.

We are aware of:

• other companies engaging

• competitive activity

• potential timelines

But this information is:

secondary

The primary driver remains:

whether we believe the asset can become a drug

A Real-World Pattern

In one instance, we had prior discussions with a company and had identified specific data gaps.

At a subsequent interaction, they returned with:

• new preclinical data

• clear evidence addressing those gaps

• a stronger case for translatability
  

This changed internal conviction.

Advocacy increased.

Momentum followed.

In another case, a company had pivoted into a therapeutic area that was aligned with our strategy and had generated early, promising preclinical data.

We had not previously engaged with them.

There was no attempt to create urgency.

No signaling of external interest.

Just:

• a clearly defined asset

• relevant data

• strategic alignment
  

That was sufficient to initiate deeper evaluation.

What Tends Not to Be Helpful

By contrast, the following patterns are less effective:

• signaling external interest without new data

• requesting meetings without meaningful progress

• attempting to accelerate timelines without resolving uncertainty
  

These do not create momentum.

They create friction.

Connecting Back to First Principles

This ties back to the central idea across all of the articles:

Global pharma is a capital allocation system under uncertainty.

We allocate capital based on:

• risk

• conviction

• comparative opportunity

Not:

• urgency

• signaling

• perceived competition

What This Means in Practice

If the goal is to accelerate engagement, the most effective path is:

• generate new data

• resolve key uncertainties

• increase PTRS

• strengthen the case that this can become a drug
  

Everything else is secondary.

Executive Takeaway

Attempts to create urgency do not accelerate pharma decisions.

The only reliable way to move a decision forward is to generate data that meaningfully reduces uncertainty and increases conviction.

Progress—not pressure—is what drives momentum.

Global pharma evaluates drug opportunities through the lens of:

• uncertainty reduction

• probability of technical and regulatory success (PTRS)

• capital allocation under uncertainty

Drug assets fit naturally into this framework.

Platforms do not—at least not initially.

For the purpose of this article, I am using “drug” and “asset” interchangeably”.

This is part of a series on how pharma actually makes decisions.

Series Navigation:

1. What Pharma Is Actually Evaluating When You Ask for a Partnership

2. Why Most Academic Discoveries Do Not Become Partnerships

3. Inside Pharma: How Advocacy Actually Works

4. Partnership Structures Are Not What You Think They Are

5. Platform vs Asset: Why Pharma Almost Always Chooses the Asset ← You are here

6. Why Creating FOMO Does Not Work in Pharma Partnering
   

What Pharma Is Actually Buying

At its core, pharma is in the business of developing and selling drugs.

Not technologies. Not capabilities. Not platforms.

Drugs.

This distinction is not philosophical—it is operational.

A drug has:

• a defined mechanism of action

• a target indication

• a development path

• a potential Target Product Profile (TPP)
  

It can be evaluated directly within the framework described in:

• What Pharma is Actually Evaluating

• How Much Data Is Enough?

It has:

• definable risk

• measurable progress

• a path to value creation

A platform, by contrast, is a capability.

It is a statement that:

“We can generate drugs.”

The Core Tension

The challenge is not that platforms are uninteresting.

It is that:

platforms do not have a TPP

They do not represent a drug.

They represent the potential to create drugs.

So from a pharma perspective, the immediate questions become:

• What will this actually produce?

• How reliably can it produce it?

• How differentiated will those outputs be?

Until those questions are answered, the platform remains:

a promise

Why Platform Pitches Often Struggle

A common pattern is:

A company presents a compelling technology and emphasizes:

• breadth

• flexibility

• multiple applications

But without:

• a defined asset

• a specific indication

• data tied to a product path
  

there is nothing to evaluate in a drug development context.

This is why many platform pitches feel like:

technology in search of a drug

The Valuation Problem

This creates a fundamental issue:

Pharma valuation frameworks are built around:

• assets

• TPPs

• probability-adjusted outcomes
  

We are used to asking:

• What is the probability this becomes a drug?

• What is the potential clinical and commercial impact?

• What are the projected costs to manufacture and sell the drug?

• What risks remain?
  

A platform does not map cleanly to these questions.

Because:

• it does not yet have a defined product

• it does not yet have a probability-adjusted path

• its does not yet have anything to manufacture

• it does not yet have clear, bounded risk
  

So what remains is:

the promise that it might generate something valuable

That is inherently difficult to value.

Why “Platform-Only” Strategies Struggle

When a company presents only the platform:

• without a clear drug path

• without drug-like outputs

• without evidence of differentiation at the asset level
  

we are left with:

nothing to underwrite

We are not in the business of funding exploration in the abstract.

We are in the business of:

building drugs

What Pharma Actually Needs to See

For a platform to become actionable, we need to see:

proof of output

This can take several forms:

• a lead asset

• multiple validated hits

• consistent generation of molecules with desired properties
  

But the key requirement is:

evidence that the platform produces outputs that are meaningfully better than existing approaches

Not just novel.

Better.

Differentiation Still Applies

Everything we discussed in Article 1 still applies.

We still ask:

• Is the biology valid?

• Is the approach differentiated?

• Can it be translated into a drug?
  

A platform does not bypass these questions.

It must answer them—through its outputs.

Where Platforms Actually Work

Platforms can and do work—but under specific conditions.

1. Demonstrated, Repeatable Output

Not a single success.

Repeatability.

The ability to show that:

this is not an isolated result—it is a capability

2. Clear, Measurable Differentiation

The platform must produce:

• molecules others cannot generate

• improved selectivity or potency

• better safety profiles

• access to new modalities
  

There must be a clear “why this is better”

3. Access to Previously Inaccessible Biology

Platforms are most powerful when they enable:

• targeting previously undruggable biology

• new mechanisms of action

• novel therapeutic approaches
  

This is where the upside is most compelling.

4. Validation Through Assets

This is the most important point.

Platforms become credible when they produce:

assets that can be evaluated within a drug development framework

The Most Effective Strategy for Platform Companies

The most effective platform companies do not lead with the platform.

They lead with:

an asset generated by the platform

They show:

• what the platform produced

• why it is differentiated

• how it compares to existing approaches
  

And then:

use that asset to validate the platform

Why This Matters for Partnering

From a partnering perspective, this reframes the discussion.

We are not evaluating:

“Is this platform interesting?”

We are evaluating:

“Does this platform produce assets we would want to develop as drugs?”

A More Subtle Point on Timing

Early-stage platform companies often believe:

• they should partner early

• they should monetize the platform directly
  

In practice:

the fastest path to a meaningful partnership is often to build an asset first

Because:

• it reduces uncertainty

• it creates something we can evaluate

• it anchors the discussion in a product
  

Connecting Back to Capital Allocation

This ties directly to the core principle:

Global pharma is a capital allocation system under uncertainty.

We allocate capital to:

• assets

• with defined risk

• with measurable PTRS

• with a path to becoming drugs
  

Platforms must eventually fit into that system.

What This Means in Practice

If you believe you have a platform:

• develop an asset

• demonstrate differentiation

• generate data that reduces uncertainty

• show how your output compares to existing approaches
  

Do not expect pharma to:

• value the platform in isolation

• underwrite the promise

• fund exploration without a product path
  

Executive Takeaway

Platforms are powerful—but only when they are anchored in outputs.

If you want pharma engagement, the most effective way to position a platform is to demonstrate that it can generate a differentiated asset with a credible path to becoming a drug.

How do partnerships actually get structured?

From the outside, deal structures often appear to be the result of negotiation, leverage, precedent, or even timing.

From the inside, that is not how it works.

This is part of a series on how pharma actually makes decisions.

Series Navigation:

1. What Pharma Is Actually Evaluating When You Ask for a Partnership

2. Why Most Academic Discoveries Do Not Become Partnerships

3. Inside Pharma: How Advocacy Actually Works

4. Partnership Structures Are Not What You Think They Are ← You are here

5. Platform vs Asset: Why Pharma Almost Always Chooses the Asset

Why Creating FOMO Does Not Work in Pharma Partnering

Structure Is an Output of Risk

Partnership structure is not the starting point of a discussion.

It is the output of risk.

More specifically, it reflects:

how much uncertainty has been reduced—and how much remains

This ties directly back to what we discussed in:

• What Pharma is Actually Evaluating

• Inside Pharma: How Advocacy Actually Works

• How Much Data is Enough?
  

As uncertainty is reduced and PTRS increases:

• internal conviction increases

• willingness to invest resources increases

• flexibility in structure increases
  

Structure evolves as a consequence.

The Sequence Matters

One of the most common misunderstandings is that structure can be optimized independently.

In reality, structure follows a sequence:

1. Strategic alignment

2. Scientific evaluation

3. Internal advocacy

4. Conviction (increase in PTRS)

5. Structure
   

If you attempt to begin at step 5, the process breaks down.

Early Engagement: Tools, Not Partnerships

At early stages, what are often referred to as “partnerships” are not partnerships in the strategic sense.

They are tools that allow us to evaluate and derisk an opportunity.

CDA (Confidential Disclosure Agreement)

A CDA is not a partnership.

It is a mechanism that allows us to invest additional time and internal resources to evaluate an opportunity more deeply.

It reflects a decision to:

spend time—not deploy capital

A CDA is only put in place after we have seen sufficient non-confidential information to justify that investment of time.

MTA (Material Transfer Agreement)

An MTA allows for:

• transfer of materials

• execution of defined experiments
  

We use MTAs when:

• there is a specific question we want to answer

• we believe answering that question could meaningfully reduce uncertainty

• we are willing to generate data to test that belief
  

Research Collaboration

Research collaborations often overlap with MTAs, and in some cases include elements of both.

They are used when:

• there are clearly defined scientific questions

• generating data could materially increase PTRS

• we want to help shape or accelerate the development of the asset
  

Importantly:

these are not exploratory exercises

They are targeted efforts to move an asset forward along the uncertainty reduction curve

We do not enter into MTAs or research collaborations for “interesting science.”

We do so when:

we believe the asset has the potential to become a drug
and additional data could change our level of conviction

The Role of Option Agreements

Option agreements are frequently misunderstood.

At a basic level, an option is a financial instrument that provides:

the right—but not the obligation—to enter into a future transaction

In pharma partnering, this translates to:

• pharma pays for the right to make a future decision

• that decision is contingent on future data
  

An option structure typically includes:

• an upfront payment for the option

• a defined period during which data will be generated

• pre-specified or partially defined terms for a future license
  
  

What an Option Actually Does

An option allows us to:

• stay close to an asset

• continue evaluating it

• allow additional data to be generated

• defer a larger capital commitment
  
  

It is a way to:

manage risk while preserving access

When Options Make Sense

Options are appropriate when:

• there is promising early data

• there are still meaningful uncertainties

• additional data could significantly increase PTRS

In this scenario, the option allows us to:

participate in the upside while continuing to reduce uncertainty

When Options Do Not Make Sense

If we already have:

• high conviction

• sufficient data

• alignment to proceed
  

Then an option is unnecessary.

In those cases:

we would move directly toward a licensing agreement

Using an option in that context would add unnecessary complexity without reducing meaningful risk.

Licensing vs. Acquisition

At a high level:

• Licensing = we rent the risk

• Acquisition = we buy the risk
  

In early-stage settings, licensing is typically preferred.

Because:

• uncertainty remains high

• flexibility is valuable

• capital efficiency matters
  

Acquisition implies a much higher level of conviction and significantly lower perceived risk.

Why Founders Misinterpret Deal Structures

A common pattern is that founders optimize for:

• upfront payments

• total deal value

• precedent transactions
  

But this misses the core driver:

not all assets at the same stage are equal

Two assets at the same stage can have dramatically different value depending on:

• the quality of pre-IND data

• the degree of uncertainty reduction

• PTRS

• IP strength

• manufacturability (CMC)

• competitive positioning
  
  

Structure is not determined by stage.

It is determined by:

how much risk has been removed

The Sponsored Research Misconception

Sponsored Research Agreements (SRAs) are one of the most misunderstood structures.

From an academic perspective:

• they provide funding

• they support continued research
  
  

From a pharma perspective:

they must be justified as a capital allocation decision toward building a drug

There are two fundamental points of tension:

1. Publication

Academics are expected to publish.

Pharma must protect competitive advantage.

If we fund research that generates meaningful results:

we will not want those results to be made public

2. IP Ownership

Under the Bayh–Dole framework:

• institutions typically own IP generated using federal funding
  
  

However, from a pharma perspective:

if we fund the development of a drug, we must control the resulting IP

If the structure results in:

• pharma funding research

• while the academic institution owns or co-owns the resulting IP
  

then this often does not make sense for us.

In many cases, it is more rational for pharma to:

• conduct the work internally
  or

• engage with a commercial entity where IP alignment is clear
  

Structure Reflects Conviction

At every stage, structure reflects:

• the level of internal conviction

• the amount of remaining uncertainty

• the relative attractiveness of the opportunity within the portfolio
  

You cannot negotiate your way into a better structure without:

improving the underlying asset

What This Means in Practice

If you want to influence deal structure:

• generate better data

• reduce key uncertainties

• increase PTRS

• demonstrate a credible path to a drug
  

Everything else is secondary.

Executive Takeaway

If you are optimizing for deal terms before reducing scientific and development risk, you are solving the wrong problem.

Structure is not negotiated into existence—it emerges from conviction.

The fastest way to improve a deal is to improve the data.

How do decisions about early stage assets actually get made inside pharma?

From the outside, decisions can appear opaque—driven by relationships, timing, or negotiation dynamics.

From the inside, the process is more structured.

At its core, it is a process of building conviction.

That process is what I refer to as advocacy.

This is part of a series on how pharma actually makes decisions.

Series Navigation:

1. What Pharma Is Actually Evaluating When You Ask for a Partnership

2. Why Most Academic Discoveries Do Not Become Partnerships

3. Inside Pharma: How Advocacy Actually Works ← You are here

4. Partnership Structures Are Not What You Think They Are

5. Platform vs Asset: Why Pharma Almost Always Chooses the Asset

6. Why Creating FOMO Does Not Work in Pharma Partnering
   
   

What Advocacy Actually Is

Advocacy is the internal process through which an opportunity gains support, alignment, and ultimately, conviction to proceed with a licensing agreement/acquisition/investment.

It does not happen in a single meeting.

It is built over time through:

• repeated interactions with different stakeholders

• increasing data

• progressive resolution of uncertainty
  

Where Advocacy Begins: Non-Confidential Discussions

The process begins with non-confidential discussions.

At this stage, we are evaluating:

• mechanism of action

• discovery validation

• differentiation

• early evidence of translatability

How Much Data is Enough? discusses the type of data we seek in a non-confidential discussion.

This is not yet a deep dive.

It is an initial assessment of:

Is there enough data here to justify investing more time?

If the answer is no, the process stops here.

If the answer is yes, we move forward.

Remaining in stealth or taking an exceedingly secretive approach to sharing initial data makes it extremely difficult for us to justify investing more time in evaluating your program.

The First Internal Inflection Point: Debrief

After the initial non-confidential discussion, we have an internal debrief between the Search & Evaluation team and Subject Matter Experts.

This is a critical moment.

It is where:

• reactions are shared

• skepticism is voiced

• key uncertainties are identified
  

This is not a formality. Nor is this linear or a one-off, internal conversation.

It is where early advocacy either begins—or fails.

The First Required Alignment

The most important alignment at this stage is between:

• disease area experts (external innovation / biology)

• drug discovery scientists (what it takes to turn chemical matter into a drug)
  

Both perspectives are required.

If the biology is interesting but not druggable → it stops.

If the chemistry is promising but the biology is weak → it stops.

If both align:

advocacy can begin

From Interest to Alignment

If initial reactions are positive, the next step is to move from:

interest → alignment

This is the most important transition in the process.

Interest means:

• this is intriguing

• this is currently on-strategy

• worth further discussion
  

Alignment means:

• we believe this could become a drug

• it is worth allocating internal resources to explore further

Without alignment:

there is no path forward

CDA: A Decision to Invest Time

Once alignment begins to form, we move under a CDA (Confidential Disclosure Agreement).

A CDA is not a partnership.

It is a decision to:

invest more time and internal resources to evaluate

At this stage:

• we bring in additional experts

• we examine the data more deeply

• we pressure-test key assumptions
  
  

What We Are Trying to Resolve

This is where evaluation becomes focused.

We are trying to answer:

• Does the data hold up under scrutiny?

• Are there gaps in translatability?

• Are there early safety concerns?

• Is the differentiation durable?
  

This connects directly to:

• What Pharma is Actually Evaluating
  

• How Much Data is Enough?
  

We are asking:

Does this data meaningfully increase Probability of Technical and Regulatory Success (PTRS)?

Advocacy Builds Through Data, Not Narrative

This is one of the most important points.

Advocacy is not built exclusively through:

• compelling storytelling

• strong presentation

• enthusiasm

These components are necessary but not sufficient

Advocacy is built through:

data that reduces uncertainty

Each new dataset should answer a specific question that previously limited conviction.

Examples include, but are not limited to:

• demonstration of target engagement

• efficacy in a relevant disease model

• resolution of a PK/PD concern

• early safety signal clarification
  

As these are addressed:

• uncertainty decreases

• PTRS increases

• internal conviction strengthens

When Pharma Steps In: MTAs and Research Collaborations

In some cases, we choose to engage more directly.

This is where:

• Material Transfer Agreements (MTAs)

• Research collaborations
  

come into play.

These are not exploratory. They are not “let’s see what happens.”

They are:

targeted investments of time and expertise to generate specific data

We use them when:

• we already believe the asset could become a drug

• there are clearly defined questions that can be answered by the experiments proposed in the MTA/Research Collaboration

• answering those questions could significantly increase PTRS
  

The goal is to move the asset forward along the uncertainty reduction curve

What Drives Internal Momentum

For advocacy to build and sustain, several things must be true:

1. Strategic Alignment

The asset must remain aligned with:

• therapeutic area priorities

• modality strategy

• portfolio needs
  

This connects to: How Global Pharma Selects Strategic Focus Areas

2. Data Quality

The data must be:

• credible

• reproducible

• decision-relevant
  

Without this internal discussions stall

3. A Credible Path Forward

The team must demonstrate:

• understanding of next steps

• awareness of development requirements

• a plan to continue reducing uncertainty
  
  

This ties directly to what we discussed in Article 2.

What Kills Advocacy

Even strong opportunities can lose momentum.

The most common reasons include:

Lack of Data

Without sufficient data:

• we cannot answer key questions

• conviction cannot increase

• discussions stall
  
  

Unrealistic Financial Expectations

If expectations are misaligned too early:

• it introduces friction

• it undermines internal support

• it can stop progress before it begins
  
  

Shifting Internal Priorities

This is critical and often underappreciated.

Pharma portfolios are dynamic:

• strategy shifts

• pipeline gaps open and close

• new data changes priorities
  

Even strong external programs can be deprioritized.

Advocacy Is a Portfolio Process

We are not evaluating your asset in isolation.

We are evaluating it relative to:

• internal programs

• external opportunities

• available capital and resources
  
  

So the question becomes:

Does this rise to the level of priority within our portfolio?

What the Best Partners Do Differently

The most effective partners understand this process.

They:

• provide clear, decision-relevant data

• anticipate the next questions

• think in terms of drug development, not just discovery

• return with data that directly addresses prior feedback
  

They make it easier for us to build conviction

Executive Takeaway

Advocacy is not created through a single meeting or a compelling narrative.

It is built over time through data that resolves key uncertainties and increases PTRS.

The goal is not just to generate interest—but to drive alignment and sustain conviction within a competitive portfolio.

Further Discussion

If you’re working on a program and thinking about engaging pharma, I’m always interested in thoughtful discussions.

Author’s Note: Many academic discoveries are scientifically compelling.

They identify new biology, uncover novel mechanisms of action, and expand our understanding of disease.

And yet, only a small fraction of these discoveries ultimately become drugs.

This is not a failure of science.

It is a mismatch of design.

This is part of a series on how pharma actually makes decisions.

Series Navigation:

1. What Pharma Is Actually Evaluating When You Ask for a Partnership

2. Why Many Academic Discoveries Do Not Become Partnerships ← You are here

3. Inside Pharma: How Advocacy Actually Works

4. Partnership Structures Are Not What You Think They Are

5. Platform vs Asset: Why Pharma Almost Always Chooses the Asset

6. Why Creating FOMO Does Not Work in Pharma Partnering
   
   

A System Mismatch, Not a Scientific One

Academic research and global pharma operate under fundamentally different objectives.

Academic systems are optimized for:

• discovery

• novelty

• publication
  

Global pharma is optimized for:

• building drugs

• scaling manufacturing

• delivering therapies to patients
  

These are not the same problem. And most academic programs are not initially designed to solve the latter.

What the Best Academic Programs Do Differently

The most successful academic programs do one thing differently:

They begin—explicitly or implicitly—with a Target Product Profile (TPP).

Even if the discovery begins as basic science, the best groups quickly shift their thinking once translational potential becomes clear.

They begin asking:

What would this need to look like as a drug?

This changes everything.

It reframes experiments from:

• “Is this biology interesting?”

to:

• “Does this biology support a drug that can be safe, effective, and competitive?”
  

Where Translation Breaks Down

In practice, translation from academic discovery to drug development most often breaks down in three areas.

1. Lack of Drug-Like Properties

Biological insight is necessary but not sufficient.

To be actionable for pharma, a program must demonstrate that the biology can be translated into a drug.

This includes:

• potency

• specificity

• target engagement

• efficacy in relevant disease models

• PK/PD relationships

• early DMPK understanding

And increasingly:

• early safety signals

• evidence of a viable therapeutic index
  

These are not “late-stage” considerations.

They are early indicators of whether a program can realistically become a drug.

This ties directly to the question I explored in How Much Data is Enough

The goal is not to check every box. It is to generate enough evidence to support a credible path forward and meaningfully increase the program Probability of Technical and Regulatory Success (PTRS).

2. Incentive Mismatch

Even when the science is strong, structural misalignment can prevent partnership.

Academic environments require:

• publication

• dissemination of results

• institutional ownership of IP
  

Under the Bayh–Dole framework, inventions generated using federal funding are typically owned by the academic institution. These incentives are entirely rational within the academic system.

But they are in direct tension with pharma’s objectives.

Global pharma must:

• protect competitive advantage

• control development pathways

• retain ownership or exclusivity over key IP
  

If we fund research and generate meaningful results, we will treat that as a competitive advantage.

We will not immediately publish it.

And we will not invest significant capital into programs where we do not have clear control over the resulting IP.

This is one of the core reasons why Sponsored Research Agreements are often misunderstood.

From an academic perspective, they are a source of funding.

From a pharma perspective, they must be justified as a capital allocation decision toward building a drug.

If the structure results in pharma funding research while not controlling the outcome, it often does not make sense for us to proceed.

3. Absence of a Credible Development Path

Even with strong biology and promising early data, many programs lack a clear path forward.

We are not just evaluating what has been done.

We are evaluating:

What happens next?

This includes:

• biomarker strategy

• toxicology planning

• CMC considerations

• regulatory path

• clinical development strategy
  

This does not need to be fully built out.

But there needs to be evidence that the team is thinking beyond the current experiment.

That they understand what it will take to move toward IND and beyond.

Where Pharma Can (and Cannot) Help

There is often a belief that pharma can step in early and “fill the gaps.”

In some cases, this is true.

We may engage through:

• Material Transfer Agreements (MTAs)

• Research collaborations
  

But these are not exploratory exercises. They are targeted investments.

We only pursue them when:

• we already believe the asset could become a drug

• additional data would meaningfully increase PTRS

• the collaboration helps move the program along the uncertainty curve
  
  

We are not a substitute for a research funding agency.

We are making capital allocation decisions under uncertainty.

Why Most Programs Do Not Translate

Importantly, it is not that most academic programs are “bad.”

It is that:

They were not designed from the start to become drugs.

What Translation Actually Requires

The programs that successfully translate do something different.

They either:

• begin with the end in mind
  or

• quickly redesign themselves once translational potential is identified
  

They start behaving less like academic discovery programs and more like early drug development programs.

How This Connects to Pharma Decision-Making

From the pharma perspective, this ties directly back to:

• What Pharma is Actually Evaluating
  

• How Much Data is Enough
  
  

We are not evaluating whether the biology is novel.

We are evaluating whether it is on a credible path to becoming a drug.

Executive Takeaway

If you are operating in an academic environment, the most important shift you can make is to begin designing your program with the end drug in mind.

Incorporating a Target Product Profile early, generating evidence of drug-like properties, and thinking through the development path will materially increase the likelihood of translation.

Programs that make this shift early stand out immediately.

Further Discussion

If you’re working on a program and thinking about engaging pharma, I’m always interested in thoughtful discussions.

Closing

If this perspective is useful, I’ll continue writing about how pharma actually makes decisions.

One question comes up consistently:

How does pharma actually make decisions?

From the outside, the process can appear opaque — driven by relationships, timing, or negotiation dynamics. From the inside, it is more structured. Pharma is not evaluating your science in isolation. It is evaluating whether your asset reduces uncertainty enough to justify building a drug.

This connects directly to themes I’ve written about previously in When Should a Biotech Exit Stealth? and When Should Biotech CEOs Engage Global Pharma, where the central idea is that engagement is not about visibility—it is about readiness.

This series breaks down how global pharma organizations evaluate opportunities, build internal conviction, and allocate capital under uncertainty.

Series Navigation:

1. What Pharma Is Actually Evaluating When You Ask for a Partnership ← You are here

2. Why Most Academic Discoveries Do Not Become Partnerships

3. Inside Pharma: How Advocacy Actually Works

4. Partnership Structures Are Not What You Think They Are

5. Platform vs Asset: Why Pharma Almost Always Chooses the Asset

6. Why Creating FOMO Does Not Work in Pharma Partnering
   
   

Where Evaluation Actually Begins

Before anything else, we need to establish strategic alignment.

Is this a therapeutic area, mechanism, or modality that fits within our current priorities?

Only after this alignment is established do we begin evaluating the asset in a meaningful way.

At that point, three core uncertainties dominate:

• Biology / disease validity

• Differentiation

• Translatability
  

1. Biology / Disease Validity

Is the biology truly causal or meaningfully connected to the disease?

This can be supported by:

• genetic evidence

• human data

• reproducible disease models

Without a credible biological foundation, little else matters.

2. Differentiation

Assuming the biology is valid, the next question is:

Is this meaningfully different from everything else we have seen?

This includes:

• internal programs

• competitor pipelines

• emerging approaches

Importantly, we are not just asking if it works.

We are asking:

Does this leapfrog what already exists or what we expect will exist?

A program that looks strong today but is likely to be surpassed by the time it reaches patients is not competitive.

3. Translatability

This is where many programs fail.

The question is:

Can this biology be translated into a drug?

This is where pre-IND thinking begins, even at very early stages.

We are looking for:

• potency

• specificity

• target engagement

• efficacy in relevant disease models

• PK/PD relationships

• early DMPK understanding
  

And increasingly:

• early safety signals

• feasibility of achieving a therapeutic index
  
  

What Comes Next

Once those three uncertainties are directionally addressed, evaluation expands to include:

Safety

• early toxicity signals

• mechanism-related risks

CMC (Manufacturability)

• can this actually be made at scale?

• is the modality tractable?

CMC is often underappreciated early—but it can become a late-stage failure point if ignored.

IP (A Silent Deal Killer)

Intellectual property is often not discussed openly—but it is critical.

Weak or uncertain IP can kill a deal even when the science is strong.

Competitive and External Landscape

We are continuously asking:

• What else is being developed?

• Could something leapfrog this?

• Will this still matter in 5–10 years?

And beyond science:

• regulatory expectations evolve

• payer environments shift

• new discoveries can make current approaches obsolete
  
  

How We Actually Use the Data

All of this data is evaluated holistically.

There is no single experiment that determines success.

Instead, the question becomes:

Does this body of evidence increase our confidence that this can become a drug?

This ties directly to what I described in How Much Data is Enough?

The goal is not completeness.

It is whether the available data meaningfully increases confidence.

The Uncertainty Reduction Curve

Every experiment should move the asset along an uncertainty reduction curve.

At the pre-IND stage, the probability of technical and regulatory success (PTRS) is often in the single digits.

So the question becomes:

• Does this data increase PTRS in a meaningful way?

• Is there a credible path to continue increasing PTRS?

How Decisions Are Framed

Importantly, for assets that are strategically aligned with a priority therapeutic area of interest and with a mechanism of action we believe in, we rarely think in terms of:

• yes / no

Instead, decisions are framed as:

Continue vs. deprioritize

Because:

• programs evolve

• new data emerges

• competing programs rise and fall
  
  

An asset that is deprioritized today may return if new data changes the equation.

What Distinguishes “Interesting Science” from “This Could Be a Drug”

The difference is not the idea.

It is the data that demonstrates the idea can survive the journey to becoming a drug.

What This Means in Practice

Global pharma is fundamentally a capital allocation system operating under uncertainty.

The decision is not:

Is this interesting?

The decision is:

Is it believable that this can become a drug—and is it competitive within our portfolio?

Executive Takeaway

If you are preparing to engage pharma, the question is not whether your data is complete.

It is whether your data meaningfully reduces uncertainty and supports a credible path to a drug.

Programs that demonstrate this—even imperfectly—advance.

Programs that do not, do not.

Further Discussion

If you’re working on a program and thinking about engaging pharma, I’m always interested in thoughtful discussions.

Closing

If this perspective is useful, I’ll continue writing about how pharma actually makes decisions.

In the following Substack article, I share:

• What pharma is actually trying to accomplish at partnering conferences
• Why registrant metadata and non-confidential decks matter
• The most common mistake in meeting invitations
• What genuinely shifts internal conviction
• What works — and what doesn’t

If you are planning to attend any conference with a structured 1:1 partnering system, this may change how you prepare.

What Pharma Is Trying to Accomplish?

At large conferences with structured 1:1 partnering systems, thousands of companies participate. From inside global pharma, these meetings are not networking events. They are portfolio checkpoints.

With limited time and far more invitations than we can accept, triage is unavoidable.

The real question is not, “Would we like to meet this company?”
It is, “Is this meeting likely to change conviction?”

Partnering meetings generally serve three purposes.

1. Identify new on-strategy assets
Strategic alignment is the first filter. If an asset does not align with publicly stated therapeutic priorities, it is unlikely to progress.

2. Track progress
If we have previously engaged, conferences are efficient checkpoints. We are looking for new data that meaningfully de-risk the asset.

3. Build internal momentum
Some meetings occur after prior scientific review and are designed to introduce the asset to additional stakeholders.

Not every meeting is exploratory. Understanding which category yours falls into matters.

Why Triage Exists?

Scale drives prioritization.

When thousands of companies register, pharma teams must filter quickly. Early screening focuses on:

- Strategic fit
- Therapeutic area
- Stage of development
- Presence of meaningful discovery or preclinical data

If these cannot be determined from your profile and non-confidential materials, the meeting is unlikely to be prioritized.

Given constrained time, we will typically choose to meet with a company that appears nearly aligned rather than take a meeting with a complete unknown.

The Role of Registrant Information

Registrant metadata matters. A lot.

If your profile does not clearly state:

- Therapeutic area
- Disease indication
- Description of the asset or mechanism
- Development stage
- Summary of discovery and preclinical work

there is little for us to evaluate when we triage.

A concise, non-confidential deck is essential.

Practical guidance:

- Register early
- Complete your profile thoroughly
- Clearly describe indication, mechanism, and stage
- Summarize key experiments
- Attach a non-confidential deck
- Indicate availability early

Planning and screening begin months in advance. Incomplete or late submissions reduce visibility.

What Works

Three elements consistently rise to the top of triage.

1. Strategic alignment
The most common mistake in registration and invitations is failing to communicate whether the asset is even on-strategy.

2. Clear, credible data
We are looking for a reason to believe the asset can become a drug. How Much Data is Enough?

3. Specific progress updates
For follow-up meetings, state:
- Date of last interaction
- Who you met
- Feedback received
- Data generated since then

Perfection is not required. Credibility and progress are.

What Does Not Work

Patterns that lower prioritization include, but are not limited to:

- No description of the asset or therapeutic area
- No non-confidential deck
- Full stealth with no high-level details or being overly secretive
- Requesting a meeting without assessing strategic alignment

Stealth may be appropriate in certain phases. But if nothing can be shared at a high level, meaningful evaluation is impossible.

Closing Perspective

As discussed in When Should Biotech CEOS Engage Global Pharma, engagement is most productive when it creates momentum.

Partnering conferences are not auditions. They are portfolio checkpoints.

The companies that consistently break through demonstrate alignment, clarity, and credible progress toward building a real drug.

Partnering conferences are not about access.
They are about conviction.

Authors Note: In the previous article, How Much Data is Enough?, I wrote about the minimum data thresholds that enable meaningful engagement with Pharma.

In Part III, I discuss provide actionable suggestions to engage in a way that supports productive dialogue.

PART III

By the time outreach occurs, two conditions should be satisfied:

1. Strategic alignment

   1. From Interest to Alignment: How Biotech CEOs Should Engage Global Pharma

   2. How Global Pharma Selects Strategic Focus Areas
      

2. Credible scientific and operational readiness

   1. How Much Data Is Enough?
      

Execution now determines whether discussions advance constructively.

Enable Cross-Functional Dialogue

Programs advance when cross-functional alignment is possible.

Support that process:

• Provide downloadable, non-confidential PDFs

• Avoid login barriers
  

• Anticipate clinical, regulatory, commercial, and manufacturing questions
  

• Present materials that can be easily shared internally
  
  If materials cannot circulate, discussion stalls.

Be Precise and Strategic

Effective outreach:

• Explicitly connects your program to stated strategy
  

• Summarizes key data succinctly
  

• Includes forwardable materials
  

• Requests a focused introductory discussion
  

What is often ignored:

• Indications clearly off strategy
  

• Broad platform narratives without supporting data
  

• Generic outreach
  

Precision signals executive maturity.

Recognize That Interest Evolves

Portfolio priorities shift as data emerge and internal programs progress.

A “no” may reflect timing.
A “yes” may reflect current alignment rather than long-term commitment.

Engage with that fluidity in mind:

• Clarify whether feedback reflects structural or temporal considerations
  

• Re-engage after meaningful data inflection points
  

• Maintain appropriate continuity
  

Closing Perspective

Engagement with global pharma is not simply an introduction.

It is entry into a structured decision environment shaped by strategy, scientific conviction, cross-functional review, and long-term portfolio considerations.

Effective CEOs position their programs to withstand that review before initiating dialogue.

When strategy, evidence, and execution align, engagement becomes productive.

When they do not, it becomes premature.

Authors Note: In a previous article, When Should Biotech CEOs Engage Global Pharma, I wrote that being on-strategy does not guarantee engagement. It opens the door to evaluation.

In Part II, we examine the data that sustains that evaluation.

This is the second of a three part series

PART II

How Much Data Is Enough?

Minimum Credibility Thresholds for Engaging Pharma

Once strategic alignment is confirmed, attention turns to evidence.

The internal question becomes:

Is there sufficient reason to believe this can become a viable drug candidate?

At this stage, organizations typically conduct light diligence. The goal is not partnership. It is to determine whether deeper scientific and operational review is warranted.

Conviction generally requires credibility across three domains: Scientific Validity, Translational Plausibility, and Development Feasibility

1. Scientific Validity

Programs must demonstrate biological effect beyond hypothesis.

Expectations often include:

• In vivo efficacy in a relevant model
  

• Clear potency and specificity
  

• Evidence of target engagement
  

• Early signals around therapeutic window
  
  

In vitro data alone rarely justifies escalation to broader internal review.

Model quality matters because it shapes how clinical and translational leaders assess risk.

2. Translational Plausibility

Evaluation quickly expands beyond preclinical signal.

Cross-functional teams consider:

• Human genetic or clinical validation
  

• Historical success or failure of similar mechanisms
  

• Competitive landscape timing
  

• Biomarker strategy
  

• Emerging PK/PD linkage
  

The strength of target validation influences how much additional data are required.

Well-validated targets aligned with strategy may justify earlier engagement.

Novel biology requires stronger evidence to support internal confidence.

The central question is:

Has enough uncertainty been reduced to justify meaningful internal attention?

3. Development Feasibility

Strong biology must be accompanied by a credible path forward.

Internal evaluation considers:

• CMC feasibility
  

• Manufacturability scalability
  

• Molecular complexity and formulation considerations
  

• Early tolerability/toxicity signals
  

• Differentiation and IP defensibility
  

Full IND packages are not required at this stage. But there must be a plausible and realistic development path.

Programs that are biologically intriguing but operationally fragile often struggle to advance internally.

CEO Actions Before Engagement

• Demonstrate in vivo efficacy in a defensible model
  

• Show potency, target engagement, and specificity
  

• Clarify translational and biomarker strategy
  

• Provide emerging PK/PD linkage where possible
  

• Outline a credible CMC pathway
  

• Articulate differentiation clearly
  

• Anticipate cross-functional questions
  
  

Once sufficient confidence is established, execution determines trajectory.

In Part III, we focus on how to engage in a way that supports productive dialogue.

Strategic priorities are regularly recalibrated through portfolio reviews and cross-functional governance discussions involving clinical development, regulatory strategy, commercial leadership, manufacturing, and finance. Strategy is not static. It evolves as data emerge, competitive landscapes shift, and internal priorities are reassessed.

This three part series builds on that foundation.

PART I

Why Most Biotech Outreach to Pharma Fails: Strategy Is the First Filter

If strategy is dynamic, engagement timing must also be dynamic.

External innovation decisions are shaped not only by scientific interest, but by portfolio priorities, development sequencing, and the availability of internal expertise.

Before science is debated, one question is asked:

Is this on strategy right now?

If the answer is no, the conversation rarely advances — regardless of data quality. Biotech CEO’s should consider reaching out to Global Pharma once they have determined whether their program is currently on strategy.

My previous article, From Interest to Alignment: How Biotech CEOs Should Engage Global Pharma, provides a checklist on how to determine if your program is on strategy.

Strategic Triage

Global pharma organizations operate within defined parameters:

• Therapeutic area focus

• Modality platforms

• Existing pipeline commitments

• Competitive landscape positioning

Those parameters are reinforced through governance forums where cross-functional leaders assess not just what is promising, but what fits.

Most inbound opportunities fail at this first filter. Not because the science lacks merit but because the strategic focus is elsewhere.

Portfolio Context Begins Early

Even early discovery programs are evaluated within a broader portfolio lens.

Global Pharma Leaders ask (and you should be prepared to answer):

• Does this strengthen our long-term position?

• Can it scale beyond an initial indication?

• Is differentiation durable?

• How does it compare to internal or competing programs?

Novelty may create curiosity but strategic fit sustains internal discussion.

CEO Actions Before Outreach

• Confirm the indication aligns with current strategic priorities

• Validate modality and platform fit

• Articulate longer-term portfolio contribution

• Reassess alignment regularly as strategy evolves

Passing strategy does not guarantee engagement. It opens the door to evaluation.

In Part II, we examine the data that sustains that evaluation.

The goal of this article is to provide practical guidance on what this understanding means in practice, particularly for biotech CEOs preparing to engage global pharma teams. The recommendations that follow are derived directly from how strategy is formed and debated inside large pharmaceutical organizations, and are intended to help founders engage with greater clarity, timing, and strategic alignment.

Review this checklist before outreach, data updates, or conference meetings with global pharma teams.

1. Treat Strategy as a Living System

Global pharma strategy is continuously recalibrated.
- Review corporate strategy web pages, R&D days, and earnings calls.
- Confirm your understanding with Pharma Search & Evaluation/External Innovation folks.
- Refresh your view at least twice per year.

-Determine whether your asset is ‘on-strategy’.

Why this matters:
Static understanding leads to mistimed engagement.

2. Frame Your Program as a Portfolio Contributor

Even early assets are evaluated in a future portfolio context.

Pressure-test:
- Can this scale beyond the first indication?
- Is durability and differentiation explicit?
- Does this still matter in 5–10 years?

Why this matters:
Novelty attracts interest; portfolio relevance sustains it.

3. Assume Interest Is Time-Bound

A “no” is rarely permanent. A “yes” rarely is either.

Engage accordingly:
- Seek guidance if the feedback as a snapshot, or a verdict.
- If a snapshot, re-engage after meaningful data inflection points.
- Ask if naintaining light continuity even without alignment would be productive.

Why this matters:
Strategic fit evolves as evidence and portfolios evolve.

4. Acknowledge Financial Stewardship Explicitly

Growth and capital discipline shape every decision.

Be credible:
- Frame scale and sustainability clearly.
- Avoid positioning that implies marginal value.

Why this matters:
Capital constraints are always present, even when unstated.

5. Optimize for Consensus, Not Sponsorship

No single person owns strategy.

Prepare for reality:
- Anticipate clinical, regulatory, commercial, and manufacturing questions.
- Provide non-confidential materials others can use internally.
- A sponsor is helpful to move things forward but consensus is required at the end of the day.

Why this matters:
Programs advance when consensus is possible.

6. Time Engagement to Enable Real Debate

Early conversations matter. Evidence matters more.

Engage when:
- Data support a substantive discussion.
- Limits of current data are clear.
- Premature conclusions are avoided.

Why this matters:
Strategy evolves through informed debate, not early commitment.

Closing Perspective

This checklist is not about predicting strategy. It is about engaging in a way that reflects how strategy is actually formed.

For biotech CEOs, this improves timing and framing. For global pharma leaders, it supports clearer, more productive dialogue.

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Author’s Notes:

1. On November 20, 2025, I spoke at the UC Berkeley Bakar Labs during a Lunch and Learn session. The audience of biotech entrepreneurs asked several thoughtful questions, including “How does global pharma actually decide where to focus strategically, and how often do those priorities change?”. This article is written as a direct response to that question. It reflects my experience inside global pharmaceutical strategy and business development, as well as ongoing dialogue with founders, scientists, and operators across the innovation ecosystem. In the coming months, I plan to follow up with additional pieces addressing other questions raised during that session.

2. The follow-on article “From Interest to Alignment: How Biotech CEOs Should Engage Global Pharma” will translate these strategic dynamics into practical recommendations for biotech CEOs navigating conversations with global pharma.

Strategy Is a System, Not a Static List

For biotech founders, pharma strategy can feel opaque. Priorities appear to shift. Feedback evolves. Programs that once generated interest may go quiet. These perceptions are understandable.

Global pharma strategy is neither arbitrary nor static. It is deliberately adaptive, shaped by science, patient need, financial stewardship, and the obligation to build durable long-term value.

There are enduring commitments, but priorities are continually refined based on advances in biological understanding, emerging clinical data, competitive dynamics, portfolio balance, and capital allocation. When a program is described as “out of strategy,” it rarely reflects a judgment on scientific quality. More often, it reflects where attention and resources are being allocated at that moment.

Financial Stewardship Shapes Strategic Focus

At scale, global pharmaceutical companies prioritize opportunities capable of supporting multi-billion-dollar value creation, market leadership, lifecycle durability, and meaningful differentiation. Programs meeting these criteria are often first-in-class or best-in-class and frequently deliver transformative patient benefit.

Why Strategic Priorities Appear to Change

Strategic evolution in global pharma is most visible through therapeutic area and modality focus. Recent examples include Johnson & Johnson’s 2023 exit from Infectious Diseases and Vaccines, Roche’s continued shift toward biomarker-defined oncology strategies, Pfizer’s expansion of platform technologies across therapeutic areas, and Novartis’ sharpening of focus on select high-impact therapeutic areas. From the outside, these moves can look like pivots. From the inside, they represent progressive refinement guided by data, competition, and capital discipline.

Strategy Advances Through Debate and Consensus

No single individual owns strategy at scale. Direction emerges through cross-functional dialogue spanning research, clinical, regulatory, commercial, and finance teams. Programs advance when they can be rigorously supported with data and defended within a competitive portfolio environment.

Closing Perspective

From the outside, global pharma strategy can seem difficult to read. From the inside, it is careful, iterative, and shaped by responsibilities that extend beyond a single program.

Clearer understanding of how strategy is formed does not guarantee alignment, but it creates the conditions for better conversations, better timing, and more productive partnerships.