Not one, but many: developing a multi-indication pricing model for medicines in Belgium.

Back ground: Current pricing and reimbursement models that focus on one indication at a time are not suited to address the market access of multi-indication medicines. Therefore, the aim of this study is to co-create with Belgian stakeholders a multi-indication pricing model and procedural pathway, to identify conditions for implementation, and to illustrate the multi-indication pricing model with a case study. Methods: Different multi-indication pricing models were identified from the literature, case studies and pilots in other countries. Semi-structured interviews were conducted with 21 representatives from the National Institute for Health and Disability Insurance, insurance funds, clinicians, patients, the policy cell of the Minister of Health, pharmaceutical industry and academia. These provided insight in the opinions of stakeholders about possible multi-indication pricing models and their feasibility in the Belgian context. Agreement on the preferred multi-indication pricing model and procedural pathway was reached in a multi-stakeholder round table. Results: The international review generated four main multi-indication pricing models that vary in terms of whether a uniform price or differential prices are applied, whether prices are adjusted for the volume and/or value of the medicine in each indication, and whether a proactive or retroactive dynamic pricing approach is used. However, Belgian stakeholders preferred a fifth model, which sets a single price as the volume- and value-weighted average price across all indications at launch. Over time, the price is adapted based on volume and value of the medicine in real-life practice for each indication. To implement this model, a legal framework, horizon scanning and early dialogue, data infrastructure, an evidence plan for the medicine, technical expertise and governance model need to be developed. Conclusion: Although the multi-indication pricing model preferred by Belgian stakeholders raises the administrative burden, it allows for the price of a medicine to vary during the lifecycle based on its initial and real-life performance in multiple indications.

Augmenting THerapeutic Effectiveness Through Novel Analytics (ATHENA) - A Public and Private Partnership Project Funded by the Flemish Government (VLAIO).

The complexity and heterogeneity of cancers leads to variable responses of patients to treatments and interventions. Developing models that accurately predict patient's care pathways using prognostic and predictive biomarkers is increasingly important in both clinical practice and scientific research. The main objective of the ATHENA project is to: (1) accelerate data driven precision medicine for two use cases - bladder cancer and multiple myeloma, (2) apply distributed and privacy-preserving analytical methods/ algorithms to stratify patients (decision support), (3) help healthcare professionals deliver earlier and better targeted treatments, and (4) explore care pathway automations and improve outcomes for each patient. Challenges associated with data sharing and integration will be addressed and an appropriate federated data ecosystem will be created, enabling an interoperable foundation for data exchange, analysis and interpretation. By combining multidisciplinary expertise and tackling knowledge gaps in ATHENA, we propose a novel federated privacy preserving platform for oncology research.