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Pharmaceutical Executive
Redefining Evidence: A Paradigm Shift to Unlock Access for Innovative Therapies
Key Takeaways
- Traditional RCTs are often impractical for innovative therapies, especially in ultra-rare conditions or where long-term outcomes are needed.
- Regulatory bodies have adapted to innovative study designs, but HTA agencies and payers remain focused on avoiding false positives, risking false negatives.
Why pharma and all stakeholders in the healthcare ecosystem should undertake a fundamental shift in how evidence to support new treatments is generated and assessed.
Scientific innovation is outpacing traditional methods for assessing and valuing new medicines, particularly emerging innovative treatment modalities with the prospect to prevent, modify, and cure diseases. While the traditional approach to evidence generation relying on large randomized clinical trials (RCTs) remains the gold standard, this is ill-suited for new modalities in ultra-rare conditions, in situations where randomization is not possible, where large trials are difficult due to sophisticated interventions, or where the time required to observe final outcomes is unacceptably long.
Regulatory bodies have adapted to these challenges by accepting innovative study designs for products in high unmet medical need areas and with a strong clinical rationale for significant benefit, where traditional RCTs are difficult or impossible to implement. However, health technology assessment (HTA) agencies and payers remain focused on avoiding “false positives” (approving treatments later found less effective), demanding robust, long-term, comparative RCTs to ensure cost-effective health expenditure. While this caution aims to protect already constrained healthcare budgets, it creates a significant risk of “false negatives,” where access to potentially transformative therapies is denied due to evidence not meeting traditional expectations and, consequently, deemed insufficient. What is often overlooked however, is that while the risk of false positives can be mitigated through managed entry agreements (MAEs), false negatives will never be detected and can prevent therapies from ever reaching patients.
The divergence between regulatory and HTA/payer requirements stems from the differing mandates of the agencies. Regulatory agencies focus on evaluating safety, efficacy, and quality of medicines, while HTA bodies seek to assess comparative effectiveness over current standard of care relative to treatment cost to ensure optimal utilization of limited healthcare budgets.
While this is no simple challenge, the increasing pace of innovation calls for a shift in how we generate and assess evidence for novel therapies. Failing to do so has two consequences: first, patients suffering from debilitating or life-threatening conditions may never receive potentially life-saving therapies due to overly rigid evidence requirements. Second, the investment landscape for medical innovation is at risk, as pharmaceutical and biotechnology companies may abandon research into complex, high-risk therapeutic areas if the pathway to reimbursement remains uncertain and cost-prohibitive.
In this article, the Boston Consulting Group (BCG) Market Access Roundtable seeks to:
- Outline the key evidence challenges as scientific innovation is outpacing existing approaches for generating evidence and the requirements to assess the value of drugs.
- Explore potential solutions for these complex evidence challenges, requiring a paradigm shift in how evidence is generated and assessed.
- Seek multi-stakeholder engagement to further detail and implement proposed solutions to address the evidence challenges, while ensuring sustainable healthcare expenditure.
Convening power
The BCG Market Access Roundtable is a forum that brings together senior market access leaders and serves as a platform for an interactive discussion on industry-level topics. Roundtable members collectively select topics that are relevant but not handled in other forums and that can have either near- or long-term relevance. Members work in smaller working groups on specific topics to develop thought pieces, relevant frameworks, or policy-related publications, which are collectively ratified by the roundtable on a biannual basis. BCG hosts this roundtable and facilitates these forums and the working groups.
Current evidence paradigm no longer fit for purpose
We have identified three sets of complex evidence challenges faced by innovative therapies. We examine each challenge in turn, with relevant examples.
Challenge 1: Prolonged duration of trials to demonstrate treatment benefits on final health outcomes
RCTs have traditionally been designed to conclusively establish the efficacy and safety of therapies within a defined timeframe of two to three years. However, this approach is often impractical for emerging therapies that target long-term prevention or curative outcomes. Examples include:
- Treatments like monoclonal antibodies, designed to slow the progression of gradually progressing, chronic diseases such as early-stage Alzheimer’s disease or Parkinson’s disease.
- RNA-based drugs for rare genetic conditions, which may require decades of observation to fully demonstrate benefits.
- Curative therapies, such as gene editing for sickle cell disease, facing challenges due to the lack of a common definition of “cure” across stakeholders (e.g., remission at 5, 10, 20 years).
Another critical concern is the impact of long trial durations on patients assigned to the control arm. Many trials allow crossover of patients to the investigational treatment when they fail to respond or progress on best supportive care or placebo. This issue is exacerbated as new or alternative therapies continue to be developed during the course of these prolonged trials, further increasing the ethical concerns of withholding treatment. The requirement for long-term RCTs can, therefore, not only delay patient access but also contribute to inequities in treatment availability for those enrolled in control groups.
Regulators and HTA bodies need to balance maturity of the data and access for patients that are waiting for new treatment options. They should consider intermediate endpoints even when these have not been established as surrogate endpoints. Otherwise, the pace of innovation will be significantly reduced, and the uncertainty will make it financially and logistically unsustainable for companies to invest into these therapies, especially given that patent exclusivity may expire before long-term outcomes are realized. The high cost and long duration of traditional RCTs in these settings does not only delay access to treatments but also places a significant financial strain on healthcare systems. Without flexible and adaptive solutions, the higher cost of drug development will lead to higher prices and affordability challenges for healthcare systems.
Challenge 2: Difficulties in establishing suitable comparisons for new treatment modalities
Innovative therapies often do not fit into the traditional RCT model, requiring double-blinded randomized comparisons to an active control group. Examples of factors contributing to the challenge of establishing suitable control groups are detailed ahead.
Outdated standard-of-care (SoC) comparisons
HTA bodies often require that trials compare new therapies against SoC as described in treatment guidelines at the outset of the study. However, in areas characterized by high innovation in therapeutic modalities and mechanisms, clinical practice evolves rapidly and in different ways across regions. By the time trial data is available, the SoC used as the comparator may no longer reflect real-world clinical practice, leading to a disconnect between the trial evidence and payer expectations.
For example, in oncology, combination therapies often become the de facto standard long before they are incorporated into guidelines. A trial comparing a novel therapy to the older monotherapy SoC defined in the guidelines cannot demonstrate its value relative to the combination therapy that clinicians are now using. This misalignment complicates HTA evaluations and can result in delayed or restricted access to the therapy, even if it offers significant benefits over the outdated comparator.
Diverse and heterogeneous patient populations
RCT samples typically require very strict entry conditions to ensure homogeneity and minimize confounding factors when assessing treatment effects. While this enhances internal validity, it also means that RCT populations are often highly selective and do not accurately reflect the real-world patient population. This discrepancy is particularly problematic for innovative therapies, frequently targeting diverse and heterogeneous treatment contexts and outcomes. Examples include:
- Precision therapies such as tissue-agnostic cancer drugs depend on a shared biomarker, but patients with that biomarker may have tumors in vastly different tissues, each with unique progression patterns and outcomes. This variability makes it difficult to identify common endpoints or suitable comparator groups. Often, these biomarkers have not historically been diagnosed, so solutions relying on real-world evidence (RWE), such as external control arms from registries, cannot be pursued.
- Microbiome-based therapies must account for the high degree of variability in patients’ microbial compositions, which significantly influences treatment response. These differences complicate the creation of homogenous control groups and robust statistical comparisons.
- Gene therapies designed to target systemic disorders such as certain metabolic or neuromuscular diseases may affect multiple physiological pathways, making it challenging to isolate and measure their impact.
Variations in comorbidities, disease progression, and baseline health conditions can confound treatment effects, leading to biased or inconclusive results, complicating trial design, and questioning trial outcomes.
Challenge 3: Ethical and practical barriers to randomization
With increasing personalization of drugs, randomization to control groups can be ethically and practically problematic for certain treatments. For example, in several cancers, the majority of patients in the control group will have some mutations that can be addressed with targeted therapies, so that the comparator group will include several different therapies. The SoC will increasingly be highly specialized technologies: for example, CAR T-cell therapy is FDA-approved as the SoC for some forms of relapsed or refractory non-Hodgkin lymphoma, multiple myeloma, and adult and pediatric relapsed B-cell acute lymphoblastic leukemia. Not only is it challenging to randomize patients to these types of treatments without incurring ethical complications, the high cost of the comparator arm also increases complexity and financial burden of RCTs for new therapies in these fields.
Additionally, in oncology and other life-threatening conditions, patients often switch from control to experimental treatments, making traditional RCT analyses unreliable, as it introduces bias in survival estimates. As a separate but related challenge, rare diseases and pediatric populations often have small, vulnerable patient cohorts, raising concerns about both the feasibility and the ethics of conducting statistically powered trials.
Balancing false positives and false negatives: The role and limitations of RWE
To ensure the sustainability of healthcare expenditure, payers have been very cautious of avoiding false positives, where resources are allocated to therapies that ultimately fail to deliver the anticipated benefits. This approach is rooted in the opportunity cost principle: within constrained healthcare budgets, funding an unproven therapy diverts resources from established treatments with known value, potentially reducing overall health outcomes.
However, following this principle increases the risk of false negatives, where transformative therapies are rejected due to insufficient evidence. The risk of false positives has been increasingly mitigated through mechanisms such as MEAs. Under MEAs, such as “coverage with evidence development,” conditional market access is granted while RWE is further collected by the innovator, typically aiming to resolve uncertainty around the therapy’s efficacy and safety within three to five years.
In contrast, the risk of false negatives, cannot be similarly mitigated. When a therapy is rejected, there is no opportunity to generate real-word experience that will eventually address remaining uncertainties. As a result, patients may never gain access to the novel treatment, or access may be limited only to certain regions. We need innovative solutions to expand access to interventions with high potential benefit. This is especially important for treatments for which meaningful benefits may only become fully apparent after 10, 20, or 30 years, such as curative or preventive therapies. These solutions should be based on a scientific and reliable framework for “potential” benefit assessment. Clear criteria would need to be established, including high unmet need, lack of effective treatments, and predictable, or at least manageable, budget impact from a payer perspective. Such an approach would improve patient access while limiting the financial risk for both payers and innovators, through systematic long-term data collection and tracking.
RWE adoption in Europe has traditionally lagged compared to the US, where regulators and payers have historically integrated more readily real-world insights into decision-making. Although progress has been made, such as the National Institute for Health and Care Excellence incorporating RWE into its five-year strategic plan and the Institute for Quality and Efficiency in Healthcare recognizing the value of RWE for gene therapies and treatments for ultra-rare diseases to be generated after the initial HTA assessment, significant gaps remain.
Beyond the US and Europe, RWE adoption varies widely. China and Japan are progressively integrating RWE into regulatory and reimbursement decisions. In other large markets such as India and Brazil, interest in RWE is growing, but challenges such as data quality, regulatory clarity, and infrastructure limitations hinder full implementation. This slower uptake often results in most countries relying on data generated in the US before approving therapies. Additionally, innovative products relying on RWE to demonstrate treatment benefits generally face restrictions, including reduced pricing, restricted reimbursement, and delayed launches. This environment not only discourages innovation but also complicates the pathway for therapies to address patients’ unmet medical need.
A proposal for a new evidence paradigm
The challenges outlined call for a paradigm shift in how evidence is generated, assessed, and valued for innovative therapies. This shift should enable timely patient access to transformative treatments while maintaining the rigor needed for informed decision-making. The new evidence paradigm must address the following critical aspects:
Paradigm Shift 1: Routine data collection and dynamic pricing for long-term evidence generation and mitigating uncertainty
To address the challenge of demonstrating long-term benefits for transformative therapies, healthcare systems must adopt routine and continuous data collection practices while implementing dynamic pricing frameworks. Together, these measures can ensure timely patient access while supporting robust, incremental evidence generation.
Adoption of routine and continuous data collection systems
Integrating data collection into routine healthcare practice is essential for capturing real-world outcomes over extended timeframes. By leveraging electronic health registries and centralized databases, healthcare systems can systematically track treatment effectiveness, adverse events, and long-term durability across diverse populations. This approach minimizes reliance on prolonged clinical trials, enabling evidence to evolve dynamically. Instead of requiring continuous response demonstration, healthcare registries can focus on key milestones to track “end-of-treatment response,” such as progression-free survival or durable remission.
These outcomes can be monitored through standardized health system-wide data collection, reducing the cost of trials for innovative therapies, and, therefore, providing faster and more affordable products for healthcare systems and patients. Collaboration among regulators, HTA bodies, payers, providers, patients, caregivers, and pharmaceutical companies is critical to ensure harmonized data metrics and consistent
evaluation criteria.
Dynamic pricing to minimize restrictions for innovative drugs
Dynamic pricing provides a complementary mechanism to support incremental evidence generation. Therapies could gain initial approval and reimbursement based on early surrogate endpoints or biomarkers, with pricing adjusted as further data emerges. By tying reimbursement to real-world outcomes, it may be possible to mitigate the financial risk for payers while maintaining incentives for innovation.
Dynamic pricing would go beyond current MEA by institutionalizing iterative pre-negotiated price adjustments as part of the HTA process, rather than relying on ad-hoc negotiations on the basis of randomly chosen data points. It would align pricing with emerging RWE, incorporate broader metrics of value to assess therapeutic benefits more comprehensively, and reduce restrictions for access to innovative therapies.
As of early 2025, the FDA is considering granting accelerated approvals for ultra-rare disease therapies based on biomarker-focused trials, rather than traditional placebo-controlled trials. HTA bodies and payers should also follow suit by aligning on more systematic and innovation-friendly approaches to reimbursement. Dynamic pricing sustained by routine data collection can mitigate long-term uncertainty, reduce financial risks for healthcare systems, and foster innovation to improve patient health.
Paradigm Shift 2: Embracing RWE, advanced statistical methods, and new frameworks for evidence generation and assessment
To address challenges around finding suitable comparisons for innovative therapies, along with ethical and feasibility challenges, we propose that HTA bodies and payers broaden their evidence evaluation frameworks to incorporate modern approaches alongside traditional RCTs, recognizing their complementary value in generating robust and clinically meaningful insights while minimizing undue penalties for innovators.
Increasing use and acceptance of RWE through standard global guidelines
To fully harness the potential of RWE in addressing the limitations of traditional trial designs, its acceptance and integration into reimbursement frameworks must be expanded and standardized. Developing global guidelines for high-quality data collection, validation, and analysis is essential to ensure that RWE is evaluated consistently across regions, starting from Europe, where efforts to standardize clinical assessments are ongoing (e.g., through the EU Joint Clinical Assessment), but variability in payer requirements remains a barrier.
By embedding RWE into routine decision-making processes, HTA bodies and payers can leverage their ability to capture therapy performance in real-world settings, particularly for therapies targeting rare diseases, precision medicine, or tissue-agnostic indications but also in slowly progressing diseases over many years, such as Alzheimer’s or Parkinson’s disease, and in situations in which an early crossover due to ethical considerations has impeded robust outcomes. Harmonized practices will enable RWE to complement traditional evidence more effectively, offering a robust and standardized tool for assessing comparative effectiveness and safety while facilitating timely patient access to innovative therapies.
Expanding use of advanced statistical tools and innovative trial designs
Advanced statistical methods and trial designs have the potential to address patient heterogeneity and the challenges posed by traditional comparator groups (see Table 1 below). Innovative designs, such as basket and platform trials, provide efficient ways to study therapies across diverse populations or multiple diseases with shared biomarkers. For example, basket trials can evaluate a single therapy for patients with the same genetic mutation across different tumor types, while platform trials can support the testing of multiple therapies simultaneously within a single adaptive framework. Techniques such as adaptive randomization and patient enrichment allow trials to focus on patients most likely to benefit, ensuring meaningful results even in small or varied populations.
In addition to trial designs, advanced statistical tools have been developed by academia, but their use in HTA settings is still not common. For instance, several options have been proposed to control for treatment switching, aiming for an unconfounded estimate of treatment effect.1,2 Other methodologies, such as indirect treatment comparisons and synthetic control arms, enable the use of historical or real-world data to create robust comparators when randomization is infeasible or to develop and validate innovative endpoints in parallel to the study. Artificial intelligence (AI)-driven models can also simulate virtual control groups, providing reliable estimates of outcomes without requiring additional patient recruitment, a significant advantage in rare or heterogeneous conditions.
Leveraging new evidence assessment frameworks to capture the full value of innovative therapies
In parallel, adopting new evidence assessment frameworks is essential for enabling a comprehensive and adaptable approach to evaluating innovative drugs, incorporating broader value elements such as productivity, equity, and patient-centered outcomes. This flexibility ensures that the full value of therapies is captured, particularly in cases where diverse patient populations or novel mechanisms of action complicate standard assessments.
For instance, generalized cost-effectiveness analysis can seamlessly integrate evidence from RWE and advanced statistical analyses, enabling dynamic assessments that evolve as more data becomes available. This iterative approach ensures that therapies are evaluated in line with their real-world impact, creating a pathway for fairer and more informed reimbursement decisions. By embedding these approaches into HTA evaluations, a cohesive system can be developed to generate reliable and generalizable evidence for innovative therapies, addressing the complexities of novel treatments while ensuring timely patient access.
The proposed solutions represent a starting point for addressing the complex challenges faced by innovative drugs. While we believe they may provide initial answers, we acknowledge that implementation will not be straightforward in practice, and that multi-stakeholder and cross-disciplinary collaboration will be needed to support the development of these ideas into full-fledged solutions.
A call to action
Collaborative efforts to redefine the future of evidence generation and the potential role of European HTA bodies and payers
We are at a time of rapid evolution of our understanding of disease biology, coupled with new less invasive and often AI-supported diagnostics and novel targeted modalities to engage with specific disease pathways in a much more targeted and predictable manner. As medical innovation accelerates, traditional evidence-generation approaches may not always be feasible or necessary, and risk leaving behind potentially life-saving therapies. While “false positives” can be mitigated over time as new data emerges, “false negatives” risk permanently denying patients access to essential treatments. In light of this, we need a fundamental shift in how evidence to support new treatments is generated and assessed.
A shift in the evidence paradigm requires a collective effort from all stakeholders in the healthcare ecosystem. Pharmaceutical companies, regulatory bodies, HTA agencies, payers, patient advocacy groups, and policymakers should come together to explore and implement flexible, adaptive solutions. In particular, with the EU Joint Clinical Assessment framework emerging, there is a unique opportunity for EU HTA bodies to take the lead in shaping a more innovative, adaptable evidence paradigm to enhance patient access while also ensuring that healthcare systems remain financially viable in the long run.
We invite stakeholders across the healthcare landscape to engage in open dialogue, share expertise, and jointly develop new frameworks for evidence generation and assessment. Only through multi-stakeholder collaboration can we ensure that innovative treatments reach patients in a timely manner while maintaining the rigor and integrity required to make informed decisions in a resource-constrained environment.
Let us work together to transform challenges into opportunities, ensuring that patients can access the life-changing therapies they need, without compromising on the quality and sustainability of healthcare systems.
References
1. Latimer, N.R.; Abrams, K.R.; Lambert, P.C.; et al.Adjusting Survival Time Estimates to Account for Treatment Switching in Randomized Controlled Trials—an Economic Evaluation Context: Methods, Limitations, and Recommendations. Medical Decis Making. 2014. 34 (3), 387-402. https://pubmed.ncbi.nlm.nih.gov/24449433/
2. Henshall, C.; Latimer, N.R.; Sansom, L.; Ward, Robyn L. Treatment Switching in Cancer Trials: Issues and Proposals. Int J Technol Assess Health Care. 2016. 32 (3), 167-174. https://pubmed.ncbi.nlm.nih.gov/27624983/v
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