Five reasons biotechs need an IEP

Every asset ends up in front of at least four audiences. A regulator. An HTA body. A payer. And the clinicians or prescribers who decide which patients actually receive it.

Each of them is making a different decision, so each of them asks a different question about your asset. They have different expectations in regards to the evidence.

Most companies discover that one stakeholder at a time, in order, over several years. By the time the fourth question arrives, the study that could have answered it finished recruiting long ago.

An integrated evidence plan (IEP) is how you find out what all four stakeholders will ask while you can still do something about it.

An integrated evidence plan - done properly - satisfies every stakeholder

An IEP sets out all the evidence your asset needs, who needs to see it, and where the gaps are.

It then clearly outlines how each piece of evidence will be generated, and in what order.

The IEP covers more than trials. Randomised trials, observational studies, registries, literature synthesis, indirect comparisons, modelling and patient-reported outcomes all sit in the same plan.

It also spans functions. Clinical development, regulatory, medical affairs, health economics, market access and commercial all generate evidence. Without a shared plan, they generate it separately and inefficiently.

That separation is the problem the IEP exists to solve. Evidence has historically been generated sequentially and in silos, which produces inefficiency across the whole product lifecycle.[1]

Here are five reasons biotechs need an IEP

It identifies the evidence question each decision-maker will ask.
It finds the gaps that would change a decision, and the ones that would not.
It turns several separate studies into one.
It increases the value of your asset, by more the earlier you start.
It gets every function working to one plan.

1. It identifies the evidence question each decision-maker will ask

Different healthcare decision-makers answer different questions, and so they need different evidence.[2] Written down, the differences look small. But they are not.

Regulators authorise on quality, efficacy and safety. What they need is a positive benefit-risk balance, and a placebo-controlled randomised trial is often sufficient on its own.[2]

HTA bodies assess added benefit against the standard of care, across clinical, humanistic, economic and societal value, on patient-relevant endpoints.[2] A trial that satisfied the regulator without a relevant comparator does not answer that.

Payers ask a further question. Does the treatment deliver equal or greater benefit than the care already routinely commissioned, and does the price reflect that benefit given how many patients will be treated.[2]

Clinicians ask something different again. Is the benefit durable, does it improve quality of life, which patients should receive it, and where does it sit in the treatment pathway.

Read those four back. They are not the same questions. Evidence built for the first will not answer the last, and vice versa.

An IEP turns each decision into an explicit evidence question, written down, before anything else happens. Everything downstream is then anchored to a question somebody is genuinely going to ask.

2. It finds the gaps that would change a decision, and the ones that would not

There is almost always a gap between the evidence you hold and the evidence a decision-maker needs. An IEP finds those gaps systematically instead of by intuition.

The harder discipline is deciding which ones to close. More evidence is not automatically better. Decision theory is clear that additional information is not always worth having, and whether it is depends on what it costs and on whether the recipient will act on it.[3]

So the useful output is not an inventory of everything missing. It is a short list of the gaps that would genuinely move a decision, with an explicit note against the ones that would not.

Without that filter, evidence gets generated because it matters to the function proposing it. Silo structure leads to evidence being produced for its perceived importance to the sponsoring function, “with little regard to how the evidence will resonate with the multitude of external stakeholders”.[3]

A gap analysis that produces a shorter list than you expected has done its job.

3. It turns several separate studies into one

This is where an integrated plan usually pays for itself first.

Take a post-marketing registry. Designed once, with the minimum viable dataset agreed at the start, one registry can deliver long-term safety, durability of response and real-world effectiveness. That single study can serve a regulatory post-authorisation commitment, support a reimbursement negotiation, and answer the clinician’s question about whether the benefit lasts.

Designed three times by three functions, it becomes three studies. Or one study that satisfies nobody completely.

Comparator choice works the same way, and the stakes are arguably even higher. Choose a comparator that answers the HTA body’s question about comparative clinical and cost effectiveness, and that is also the treatment your payer already routinely commissions, and one comparison serves both. Choose them separately and you may need two, or you may find the comparison you ran is not the one the payer wanted.

That subtlety has large consequences for reimbursement, and it is invisible unless somebody is looking at all the stakeholders at once.

The failure mode is well documented. Where there is no visibility of activities across functions and geographies, local and regional teams duplicate work and waste resources.[1]

4. It increases the value of your asset, by more the earlier you start

This one has been quantified.

One analysis applied an expected net present value model to two integrated evidence plans, comparing the cash flows of a development programme with and without them.[4] Both cases are modelled rather than observed, so treat the figures as an order of magnitude rather than a promise.

In the first, an observational study was added to support a supplemental indication in one region that would accept it in place of a phase II trial. It looked like a pure extra cost, because the phase II trial was happening anyway. But the observational study read out in under a year against nearly three years for the phase II, so that region’s submission came two years earlier. The extra study cost 2.5 million dollars. The net gain was 78.3 million.

In the second, a phase IIIb trial was added to demonstrate the value of earlier diagnosis and earlier treatment. It cost 6.2 million and returned 72.8 million, a net gain of 66.6 million. The result survived heavy stress testing. The trial would have had to cost more than eleven times the estimate before the plan stopped paying for itself.

The same model was then run again for the second case, with the trial started two years earlier in the lifecycle. The gain rose to 127.8 million, nearly double.[4]

Same plan. Same study. Earlier start. Roughly twice the value.

That happens because an IEP works through a small number of levers. Getting the product available faster. Getting it adopted more steeply. Reaching more patients. Holding the position longer. Generating the evidence more efficiently. Raising the probability of approval and reimbursement.[3]

Most of those levers can only be pulled early.

5. It gets every function working to one plan

Evidence generation is a shared responsibility spread across research, clinical development, clinical operations, medical affairs, data management and health economics.[4]

Shared responsibility without a shared plan means priorities get set by whoever argues hardest, or by whoever holds the budget.[3]

An IEP replaces that with something everybody can see. One agreed set of outcomes. One agreed set of gaps. One prioritised list of activities, each with a stated reason for being on it.

The practical gain is that disagreements happen during planning, where they cost a conversation, rather than at submission, where they cost a year.

It does need governance to work. Somebody has to be accountable for cross-functional priorities, activities have to be tracked, and competing needs have to be prioritised deliberately rather than by default.[1] A plan nobody owns is a document, not a process.

How we do it

At Evidax we build integrated evidence plans using our six-step IEP Method.

Core team and scope. We form a small joint team with you. Together we agree the desired outcomes, key stakeholders, and target markets.
Landscape and stakeholder mapping. We identify your subject matter experts and establish the status of your asset, including development stage, estimand, and comparators in each target market.
Internal evidence capture. We deploy a bespoke questionnaire through the secure Evidax Workspace to capture the information you hold on your asset, including internal evidence and stakeholder correspondence.
Evidence gap analysis. We turn each desired outcome into a question that can be answered with evidence. We synthesise the relevant published and real-world evidence with Evidax TRACE and combine it with your internal evidence. Gaps are mapped to each decision-maker in a clear evidence gap matrix.
Prioritisation. We run one workshop with your subject experts to prioritise the evidence gaps. The discussion starts from what the evidence shows, not from what people assume is missing.
Integrated evidence plan. We develop a bespoke plan to fill the prioritised evidence gaps in the most efficient way possible.

Every stage is hosted on the secure Evidax Workspace, with real-time updates and full visibility for your team. The plan is not written once and filed. It changes as evidence lands.

Take home

Regulators, HTA bodies, payers and clinicians are asking four different questions. Evidence built for one of them will not answer the others.
The point of a gap analysis is not to list everything missing. It is to identify the gaps that would change a decision, and to say so about the ones that would not.
One well-designed study can serve several stakeholders at once. Designed separately by separate functions, it becomes several studies.
The commercial value has been modelled and it is large, with net gains of 66.6 and 78.3 million dollars in two modelled cases.
Timing is the biggest lever you have. The same plan started two years earlier nearly doubled its value.
A plan nobody owns is a document. Somebody has to be accountable for it, and the whole team has to be able to see it.

The best time to build an integrated evidence plan is at the start of clinical development. The second best time is now.

References

Fujii R, Nouri M, Khan M, et al. Integrated evidence generation planning: why medical affairs is a critical partner. Pharmaceutical Medicine. 2026. https://doi.org/10.1007/s40290-026-00620-2
Grueger J, Srikant V. Guidance for an effective approach to integrated evidence planning in a dynamic world. Clinical Pharmacology & Therapeutics. 2025;117(4):919-927. https://doi.org/10.1002/cpt.3556
Olson M, Capkun G. The value of evidence and its role in driving product strategy. Journal of Comparative Effectiveness Research. 2024. https://doi.org/10.57264/cer-2024-0074
DiMasi JA, Olson MS, Smith Z, Getz KA, Capkun G. Assessing the value of integrated evidence approaches in drug development. Therapeutic Innovation & Regulatory Science. 2025;59:808-816. https://doi.org/10.1007/s43441-025-00778-y