Lada Leyens, John Batchelor, Erwin De Beuckelaer, Kai Langel, Bert Hartog
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Unlocking the full potential of digital endpoints for decision making: a novel modular evidence concept enabling re-use and advancing collaboration.
Introduction: Over the last decade increasing examples indicate opportunities to measure patient functioning and its relevance for clinical and regulatory decision making via endpoints collected through digital health technologies. More recently, we have seen such measures support primary study endpoints and enable smaller trials. The field is advancing fast: validation requirements have been proposed in the literature and regulators are releasing new guidances to review these endpoints. Pharmaceutical companies are embracing collaborations to develop them and working with academia and patient organizations in their development. However, the road to validation and regulatory acceptance is lengthy. The full value of digital endpoints cannot be unlocked until better collaboration and modular evidence frameworks are developed enabling re-use of evidence and repurposing of digital endpoints.
Areas covered: This paper proposes a solution by presenting a novel modular evidence framework -the Digital Evidence Ecosystem and Protocols (DEEP)- enabling repurposing of measurement solutions, re-use of evidence, application of standards and also facilitates collaboration with health technology assessment bodies.
Expert opinion: The integration of digital endpoints in healthcare, essential for personalized and remote care, requires harmonization and transparency. The proposed novel stack model offers a modular approach, fostering collaboration and expediting the adoption in patient care.
期刊介绍:
Expert Review of Pharmacoeconomics & Outcomes Research (ISSN 1473-7167) provides expert reviews on cost-benefit and pharmacoeconomic issues relating to the clinical use of drugs and therapeutic approaches. Coverage includes pharmacoeconomics and quality-of-life research, therapeutic outcomes, evidence-based medicine and cost-benefit research. All articles are subject to rigorous peer-review.
The journal adopts the unique Expert Review article format, offering a complete overview of current thinking in a key technology area, research or clinical practice, augmented by the following sections:
Expert Opinion – a personal view of the data presented in the article, a discussion on the developments that are likely to be important in the future, and the avenues of research likely to become exciting as further studies yield more detailed results
Article Highlights – an executive summary of the author’s most critical points.