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Patient-centricity in digital measure development: co-evolution of best practice and regulatory guidance.

Authors :
Aryal, Suvekshya
Blankenship, Jennifer M.
Bachman, Shelby L.
Hwang, Soohyun
Zhai, Yaya
Richards, Jennifer C.
Clay, Ieuan
Lyden, Kate
Source :
NPJ Digital Medicine; 5/16/2024, Vol. 7 Issue 1, p1-7, 7p
Publication Year :
2024

Abstract

Digital health technologies (DHTs) have the potential to modernize drug development and clinical trial operations by remotely, passively, and continuously collecting ecologically valid evidence that is meaningful to patients' lived experiences. Such evidence holds potential for all drug development stakeholders, including regulatory agencies, as it will help create a stronger evidentiary link between approval of new therapeutics and the ultimate aim of improving patient lives. However, only a very small number of novel digital measures have matured from exploratory usage into regulatory qualification or efficacy endpoints. This shows that despite the clear potential, actually gaining regulatory agreement that a new measure is both fit-for-purpose and delivers value remains a serious challenge. One of the key stumbling blocks for developers has been the requirement to demonstrate that a digital measure is meaningful to patients. This viewpoint aims to examine the co-evolution of regulatory guidance in the United States (U.S.) and best practice for integration of DHTs into the development of clinical outcome assessments. Contextualizing guidance on meaningfulness within the larger shift towards a patient-centric drug development approach, this paper reviews the U.S. Food and Drug Administration (FDA) guidance and existing literature surrounding the development of meaningful digital measures and patient engagement, including the recent examples of rejections by the FDA that further emphasize patient-centricity in digital measures. Finally, this paper highlights remaining hurdles and provides insights into the established frameworks for development and adoption of digital measures in clinical research. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23986352
Volume :
7
Issue :
1
Database :
Complementary Index
Journal :
NPJ Digital Medicine
Publication Type :
Academic Journal
Accession number :
177311002
Full Text :
https://doi.org/10.1038/s41746-024-01110-y