What Ojemda’s Joint Clinical Assessment Reveals About the EU HTA Regulation and Europe’s New Evidence Standard ?

As the first Joint Clinical Assessment (JCA) conducted under Europe's new EU HTA Regulation, Ojemda (tovorafenib)'s evaluation is a key milestone, completed in parallel with its EMA regulatory review. In April 2026, Ojemda received conditional EU marketing authorization, enabling Ipsen to proceed with EU launches and using the JCA's outcome as a common evidence foundation for subsequent national reimbursement decisions.

Abbreviations: ATMP: Advanced Therapy Medicinal Product, EU: European Union; HTA: Health Technology Assessment, HTAR: HTA Regulation, IQWiG: Institute for Quality and Efficiency in Health Care (Germany), JCA: Joint Clinical Assessment, LGG: Low-Grade Glioma, NCPE: National Centre for Pharmacoeconomics (Ireland), PICO: Population, Intervention, Comparator, Outcome

The assessment provides valuable insights into how manufacturers should prepare their market access strategy under the evolving European HTA framework. Beyond demonstrating efficacy, developers should ensure that clinical trial endpoints are aligned with payer expectations and support comparative effectiveness assessments under the EU HTA Regulation.

Europe's first Joint Clinical Assessment (JCA) of tovorafenib (Ojemda), apart from being an inaugural test of the new EU health technology assessment (HTA) framework, it is a pointed illustration of how a single approved indication can rapidly multiply into a complex set of payer-relevant questions.

For manufacturers, the implication is straightforward: JCA outcomes are shaped well before dossier preparation begins. They are shaped far earlier, by decisions that define the evidentiary landscape long before submission. Comparator selection, anticipation of PICO (Population, Intervention, Comparators, Outcomes) requirements across Member States, evidence generation for key subpopulations or external controls, and strategies for managing uncertainty will largely determine how smoothly an assessment proceeds.

Ojemda’s pivotal evidence came from FIREFLY‑1, a single‑arm Phase II study without a concurrent control - an approach that is common in rare paediatric oncology. The JCA, however, is designed to assess relative effectiveness - not simply whether a medicine works, but how it performs compared with relevant alternatives. In the absence of a head‑to‑head trial, Ipsen submitted an unanchored Matching‑Adjusted Indirect Comparison (MAIC) to estimate relative efficacy. For patients with BRAF V600E mutations, FIREFLY‑1 data were matched to an external study of dabrafenib plus trametinib, creating a cross‑trial comparator.

While this approach was feasible, given the evidence constraints, the assessment highlighted important limitations: residual confounding, a very small effective sample size after matching, and the inherent weaknesses of non‑randomised comparisons. In practical terms, while single‑arm response data demonstrated clinical activity, they were insufficient on their own to establish a comparative advantage over existing therapies.

For developers, the takeaway is that indirect comparisons such as MAICs must be planned and executed carefully. When designed appropriately, they can support a JCA in settings where randomised trials are not feasible. Their credibility depends on access to suitable external comparator data, strong population matching, and transparent sensitivity analyses. These elements need to be incorporated into the evidence strategy early, rather than added late as a workaround.

Health technology developers can strengthen their JCA readiness by partnering with specialized evidence‑generation and market access service providers, particularly given the compressed timelines, expanded PICO scope, and methodological scrutiny introduced by the EU HTA framework. External partners bring dedicated expertise, scalable analytical capacity, and prior experience navigating multi‑country HTA expectations - capabilities that are difficult to build rapidly within a single organization. By supporting early feasibility assessments, robust indirect comparisons, and integrated evidence strategies aligned with diverse EU HTA requirements, such partnerships help reduce execution risk and improve the quality, consistency, and defensibility of JCA submissions.

The Ojemda JCA illustrates how a single regulatory label can generate a wide range of HTA questions. The final assessment scope defined eight distinct PICO comparisons across different populations and treatment pathways — spanning targeted therapy, chemotherapy regimens, and individualised approaches. Yet comparative evidence existed for only one of these eight PICOs: tovorafenib versus dabrafenib plus trametinib in BRAF V600E-mutant patients. For the remaining seven, the evidence base was descriptive only.

This reinforces that PICO scoping is not a procedural formality; it determines the evidence required to address national HTA perspectives. Comparator selection and PICO anticipation are now central to asset risk management, as gaps in any scoped comparator can materially affect HTA outcomes. Once a broad comparator set is agreed, missing data are difficult to generate in time for submission. Developers therefore need to anticipate likely PICO requirements and embed a broad comparator strategy into earlier clinical and evidence‑generation plans. Integrating these considerations into the broader market access strategy enables manufacturers to anticipate reimbursement evidence requirements much earlier in clinical development.

Tovorafenib is an orphan therapy for a rare paediatric cancer, but the JCA experience confirms that evidence expectations remain high. Assessors recognised the challenges - small patient populations, limited feasibility of randomised trials, and few treatment options - yet still required the strongest possible evidence within those constraints. Orphan status may inform context and justify alternative approaches, but it does not remove the need to demonstrate comparative benefit.

When randomised trials are not feasible, manufacturers need to pursue other evidence sources, including natural‑history data, real‑world evidence, and external control cohorts, and to articulate clearly what the data can and cannot show. These efforts are most effective when initiated early, rather than assembled close to submission. The Ojemda case suggests that while assessors are pragmatic about rare‑disease realities, they expect manufacturers to exhaust feasible options for strengthening comparative evidence. For developers of rare disease therapies, this reinforces that orphan designation does not reduce evidence expectations but instead increases the importance of innovative evidence-generation approaches and early planning.

Ojemda’s indication spans multiple BRAF alterations, and the JCA scope reflected this biological diversity by effectively separating the assessment into biomarker‑defined subpopulations. Ipsen provided an indirect comparison for the BRAF V600E subgroup and descriptive outcomes for patients with BRAF fusions or rearrangements, but comparative evidence could not be generated for all subgroups.

This illustrates that a single pooled evidence package may be insufficient when prognosis, treatment pathways, or comparators differ by subgroup. As precision medicines become more common, developers should expect HTA scrutiny at the molecular‑subgroup level and plan accordingly. That includes defining subgroup‑specific endpoints, ensuring adequate representation, and considering tailored comparator strategies - potentially supported by external data - well in advance. Selecting appropriate clinical trial endpoints for individual biomarker-defined populations becomes increasingly important as precision medicine expands and HTA evaluations become more granular.

A defining feature of the Ojemda JCA was its treatment of uncertainty. Assessors identified multiple sources, including reliance on an unanchored indirect comparison, potential unmeasured confounders, and a sharply reduced effective sample size after matching. Following the MAIC, fewer than 15 patients’ worth of data were effectively comparable, resulting in wide confidence intervals and imprecise estimates. The assessment accepted these results but cautioned against over‑interpretation as evidence of causal benefit.

Importantly, these uncertainties were made explicit. Assumptions were described, sensitivity analyses conducted, and limitations clearly stated. The experience suggests that uncertainty itself is not disqualifying; rather, its visibility and management are critical. Proactive uncertainty management - identifying limitations, quantifying their potential impact, testing assumptions, and contextualising results - allows assessors to engage with imperfect evidence more constructively. A proactive uncertainty management approach should therefore become a core component of every evidence generation strategy, particularly for innovative and precision therapies.

Abbreviations: EMA: European Medicines Agency, ESS: Effective Sample Size, HRQoL: Health-Related Quality of Life, HTA: Health Technology Assessment, HTACG: HTA Coordination Group, HTAR: HTA Regulation, IPD: Individual Patient Data, ITC: Indirect Treatment Comparison, JCA: Joint Clinical Assessment, JSC: Joint Scientific Consultation, MAIC: Matching-Adjusted Indirect Comparison, ORR: Objective Response Rate, PFS: Progression-Free Survival, PICO: Population, Intervention, Comparator, Outcome, RANO: Response Assessment in Neuro-Oncology, RWE = Real-World Evidence.

The first Joint Clinical Assessment of tovorafenib under the EU HTA Regulation underscores that successful joint HTA outcomes are rooted in early development decisions, not in dossier writing alone. The key challenges - limited head‑to‑head data, incomplete comparator coverage, subgroup constraints, and substantial uncertainty - were largely determined by upstream evidence‑planning choices. By the time of submission, these gaps could not be fully addressed.

Looking ahead, manufacturers should assume that a single EMA approval may trigger multiple HTA questions across PICOs and design their programmes to answer them. The focus shifts from “How do we prepare a JCA dossier?” to “Have we built an evidence strategy that can withstand the PICO framework?” This requires earlier investment in comparator planning, PICO‑led evidence generation, subgroup‑ready analytics, fit‑for‑purpose external data, and clear uncertainty narratives.

The Ojemda assessment highlights five pressure points for future submissions: demonstrating relative effectiveness without direct trials; covering multiple comparators; generating evidence in rare diseases; addressing molecular subgroups; and managing uncertainty transparently. These are not shortcomings of the system but the operational realities of a more harmonised and transparent HTA model. With foresight and early planning, they are manageable

As a strategic imperative, JCA readiness should be treated as an enterprise-wide priority rather than just a late-stage market access task. Indegene can support life sciences organizations on this journey. For example, by assessing current evidence and capability gaps, designing integrated evidence-generation strategies (early PICO scoping, robust indirect comparisons, Real-World Evidence plans, etc.), and strengthening cross-functional processes and training so global, regional, and local teams are aligned with JCA requirements. By translating JCA requirements into practical roadmaps, Indegene’s end-to-end, cross-disciplinary support helps organizations advance from awareness to action, ensuring their therapies are well-positioned for successful JCA outcomes and timely patient access across Europe.