Unlocking the full potential of digital endpoints for decision making: a novel modular evidence concept enabling re-use and advancing collaboration

Expert Rev Pharmacoecon Outcomes Res. 2024 Jul;24(6):731-741. doi: 10.1080/14737167.2024.2334347. Epub 2024 May 15.

Abstract

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.

Keywords: Digital endpoint; clinical research; clinical validation; digital health; digital health technology; patient focused drug development.

Publication types

  • Review

MeSH terms

  • Biomedical Technology / methods
  • Cooperative Behavior
  • Decision Making
  • Delivery of Health Care / organization & administration
  • Digital Technology
  • Drug Industry / organization & administration
  • Endpoint Determination*
  • Humans
  • Precision Medicine / methods
  • Technology Assessment, Biomedical* / methods