Evidence
decoded: the
reality check

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From regulatory hurdles to payer acceptance

It is a common pitfall in drug development to assume that regulatory approval guarantees market access. A clinical trial that successfully demonstrates safety and efficacy to the FDA or EMA has only cleared the first hurdle.

When your dossier enters the health technology assessment and reimbursement phase, the perspective changes. To support a smooth transition from clinical development to market access, evidence needs to be considered not only from a regulatory perspective, but also through the lens of multiple HTA assessors.


When is evidence actually considered robust?

Evidence is considered robust when it can withstand structural scepticism.

Conversely, evidence becomes vulnerable when statistical models rely on fragile assumptions, ambiguous methodology, or endpoints that do not translate clearly into relevant decision contexts.

Key

Focus ↓

Regulatory lens

Efficacy and safety under controlled trial conditions.

HTA & payer lens

Relative effectiveness and safety in the relevant treatment context.

Key

Success metric ↓

Regulatory lens

Demonstration of significant efficacy and an acceptable safety profile to support a positive benefit–risk assessment.

HTA & payer lens

Demonstration of comparative clinical benefit across relevant outcomes.

Key

Validity ↓

Regulatory lens

Internal validity is critical. External validity is important to support extrapolation to the intended patient population.

HTA & payer lens

Internal validity is critical. External validity and transferability to the target healthcare setting are essential.

Where comparative evidence becomes vulnerable

The quantifiability

of uncertainty

NICE

HTA reviewers accept that evidence cannot always be complete, particularly in rare diseases and targeted oncology.

But uncertainty needs to be characterised, modelled and justified.

For example, the choice of parametric survival model can materially influence long-term outcomes and cost-effectiveness. Where different extrapolation approaches produce substantially different results, the underlying clinical and statistical assumptions become critical to the assessment.

➝ Uncertainty itself is not necessarily the problem.
➝ Unexplained or poorly characterised uncertainty is.

The appropriate

comparator

G-BA & IQWiG

The relevance of comparative evidence depends on the treatment context against which an intervention is assessed.

The appropriate comparator therapy (zweckmäßige Vergleichstherapie) plays a central role in the assessment of added benefit. A global clinical programme may generate robust comparative data that do not fully address the comparator requirements of the German assessment context.

➝ Strong comparative results are only meaningful when the comparator is relevant to the decision context.

The standardisation

of joint assessments

JCA

The Joint Clinical Assessment (JCA) introduces a more coordinated European assessment of relative clinical effectiveness.

Health technology developers (HTDs) need to anticipate multiple PICO perspectives across European healthcare systems. This increases the importance of considering population, comparator, outcomes and analytical approaches early in clinical development.

➝ Evidence requirements increasingly need to be considered before beginning phase III, not only when the dossier is prepared.

The strategic realisation

Strong clinical results are only the beginning.

Evidence must remain relevant, transparent and defensible when tested against the requirements of regulators, HTA bodies and healthcare systems.

Robust evidence connects statistical rigour with decision relevance.

Explore the relevant evidence
pathways

Evidence Generation

Align evidence generation with future assessment requirements.

Build the right evidence foundation ➝

Robust Analytics

Understand how methodological choices affect uncertainty and decision confidence.

Transform data into dependable insights ➝

HTA Confidence

Explore how comparative evidence can remain relevant under critical assessment.

Support decisions with credible evidence ➝

Latest insights

Multiplicity in EU Joint Clinical Assessment

Preparing evidence for evolving assessment requirements.

Read our insight →

Utilising real-world data for EU HTA

Identifying critical evidence before it becomes a barrier.

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Polynomial-Based MAIC

Building a stronger case for successful reimbursement decisions.

Read our insight →

Our work in practice

Selected examples of complex statistical questions and how we addressed them across clinical development, HTA and market access.

Over 1,000 projects delivered.


See selected case studies ➝

Implementation of ML-NMR for Rate Outcomes

Lessons from a Recent EU HTA Submission

View scientific poster ➝

Case Snapshot ➝

Numerus invented a new MAIC methodology

Case Snapshot ➝

Hyper complex NMA successfully executed

Your next evidence challenge

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