PREFER (2016–2022) focused directly on integrating patient preferences into benefit-risk assessments across the drug lifecycle.
CENTRE FEDERAL D'EXPERTISE DES SOINS DE SANTE
Belgian federal health evidence centre specialising in benefit-risk assessment, patient preferences, and personalised clinical trial methodology.
Their core work
The Belgian Federal Knowledge Centre for Health (KCE) is a government-mandated body that produces independent scientific evidence to support healthcare policy and decision-making in Belgium. Their work spans health technology assessment, clinical methodology, and benefit-risk evaluation of medicines and medical interventions. In H2020, they contributed expertise in how patient preferences should be integrated into drug approval and lifecycle management processes, and in the methodological design of personalized clinical trials. They bridge the gap between clinical research evidence and public health policy.
What they specialise in
PERMIT (2020–2022) addressed umbrella trial methodology, patient stratification, and translational research for personalized medicine.
PERMIT keywords explicitly include patients stratification and cohorts, reflecting methodological depth in clinical data segmentation.
Machine learning appears as a keyword in PERMIT, suggesting growing use of AI methods within their clinical trial and evidence synthesis work.
KCE's institutional mandate and participation in both projects centers on translating clinical evidence into actionable policy and regulatory guidance.
How they've shifted over time
Their earliest H2020 engagement (PREFER, 2016) focused on benefit-risk methodology and the role of patient preferences in regulatory decision-making — a largely qualitative, policy-oriented domain. By 2020, with PERMIT, their work had shifted toward quantitative clinical trial methodology: patient stratification, machine learning, umbrella trials, and translational research pipelines. The trend is a clear move from policy-advisory roles toward data-driven, methodologically rigorous clinical research design.
KCE is moving from health policy advisory work toward active participation in precision medicine research, combining regulatory methodology with machine learning and adaptive trial design — making them increasingly relevant to pharma R&D consortia.
How they like to work
KCE has participated exclusively as a partner, never as consortium coordinator, which reflects their institutional role as an independent evidence body rather than a project driver. Despite only two projects, they engaged with 47 unique partners across 12 countries, suggesting they join large, multi-stakeholder consortia rather than small focused teams. This breadth indicates they are valued as a credible, neutral third-party voice on health evidence and policy methodology.
KCE collaborated with 47 unique partners across 12 countries despite only two projects — an unusually wide network for such limited participation. Their reach is European, consistent with involvement in large IMI (Innovative Medicines Initiative) and RIA consortia.
What sets them apart
KCE is one of only a small number of national health technology assessment bodies in Europe with direct H2020 research participation, giving them a rare combination of regulatory credibility and hands-on EU research experience. Their government mandate ensures independence from commercial interests, which makes them a trusted partner for benefit-risk and patient-preference work where neutrality is essential. For pharma or MedTech consortia needing a policy bridge between clinical evidence and reimbursement decisions, KCE fills a role that academic partners cannot.
Highlights from their portfolio
- PREFERA long-running IMI-funded project (2016–2022) with the largest single EC grant to KCE (EUR 252,500), addressing a pivotal regulatory question — how to formally incorporate patient preferences into drug approval decisions.
- PERMITRepresents KCE's pivot toward precision medicine, introducing machine learning and umbrella trial design into their methodological toolkit for the first time.