Planning Post-Launch Evidence Generation: Lessons from France, England and Spain.

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Tác giả: Catrin Austin, Karen Facey, Seamus Kent, Francois Meyer, Alina Pavel, Joshua Ray, Carlos Martin Saborido, Steve Williamson

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: United States : Clinical pharmacology and therapeutics , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 180762

Technological developments and innovations in regulatory pathways have meant medicinal products are increasingly associated with substantial clinical and economic uncertainties at launch. This has increased the focus on continuous evidence generation to assess the real-world value of new medicines post-launch. This paper examines Post-Launch Evidence Generation (PLEG) systems in France, Spain, and England, drawing on insights from a series of multistakeholder roundtables hosted by RWE4Decisions. These discussions provided a platform to compare national approaches to PLEG considering PLEG planning and operationalization. The roundtable events included presentations by representatives of the HTA bodies and payers in France, Spain, and England, an industry response, and multistakeholder discussions. The events highlighted that while there are differences in the products to which PLEG is applied and the way it is operationalized, there are many common challenges experienced across systems and by all stakeholders. First, there is a recognition that evidentiary needs must be anticipated earlier to avoid PLEG where possible and better plan for PLEG where needed. Second, there is a need to streamline data collection. This includes trying to make greater use of existing data sources vs. primary data collection, prioritizing collection of a small number of outcomes that directly address key uncertainties, and by improving international collaborations to streamline data collection and evidence generation across borders. Our findings suggest value in improving scientific advice processes and international collaboration to discuss key data gaps early and ensure efficient and effective evidence collection that improves the speed and quality of reimbursement and pricing decisions.
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