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

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
• digital health
• clinical research
• patient focused drug development
• clinical validation
• digital health technology

Article highlights

• 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.

• The novel modular evidence framework can support optimisations to current qualification procedures and pathways to obtain regulatory acceptance.

• The novel modular framework can also support and foster collaboration among endpoint developers and across stakeholders.

Declaration of interest

E. De beuckelaer and K. Langel are employees of affiliates belonging to Janssen: Pharmaceutical Companies of Johnson & Johnson. B. Hartog was an employee of Johnson and Johnson Innovative Medicine at the time of writing. J. Batchelor is an employee of DEEP Measures Oy. L. Leyens is a member of the Board at DEEP Measures Oy, she was an employee of F. Hoffmann-LaRoche Ltd at the time of writing the publication, since she became an employee of Takeda Pharmaceuticals International AG. Their remuneration was not dependent on, or associated with this publication. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. The DEEP patent filing [26] is owned by Janssen, Pharmaceutical Companies of Johnson & Johnson, inventors named are BH, EDb and KL; exclusive rights of use have been assigned to DEEP Measures Oy.

Acknowledgments

For supporting illustrations used in the text we gratefully acknowledge Jackie Evers.

For the section on “Qualification procedures 2.0” we would like to acknowledge the EFPIA ERAO qualification team and the Digital Endpoint joint subteam for their thought leadership in proposing optimisations to the EMA regulatory pathway of qualification of novel methodologies. Some of the ideas proposed by this team inspired the authors in that section. Specially Cathelijne de Gram, Mireille Mueller and Igor Knezevic.

Author contributions

All authors contributed equally to the following: (1) substantial contributions to the conception or design of the work; (2) drafting the work and revising it critically for important intellectual content; (3) final approval of the completed version; and (4) accountability for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.