Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials

作     者：Ratitch, Bohdana Rodriguez-Chavez, Isaac R. Dabral, Abhishek Fontanari, Adriano Vega, Julio Onorati, Francesco Vandendriessche, Benjamin Morton, Stuart Damestani, Yasaman 

作者机构：Statistics and Data Insights Bayer WestmountQC Canada Strategy Center for Decentralized Clinical Trials and Digital Medicine Drug Development Solutions Icon Plc Blue BellPA United States Global Development Operations Amgen Inc. Thousand OaksCA United States Product PatchAi S.r.l. An Alira Health Company Padua Italy Department of Medicine University of Pittsburgh PittsburghPA United States Applied Data Science Current Health A Best Buy Health Company BostonMA United States Department of Electrical Computer and Systems Engineering Case Western Reserve University ClevelandOH United States Emerging Digital Medicines Eli Lilly & Co. IndianapolisIN United States Digital Medicine Karyopharm Therapeutics NewtonMA United States 

出 版 物：《Digital Biomarkers》 (Digit. Biomarkers)

年 卷 期：2022年第6卷第3期

页      面：83-97页

核心收录：

主　　题：Biometrics 

摘      要：Background: The proliferation and increasing maturity of biometric monitoring technologies allow clinical investigators to measure the health status of trial participants in a more holistic manner, especially outside of traditional clinical settings. This includes capturing meaningful aspects of health in daily living and a more granular and objective manner compared to traditional tools in clinical settings. Summary: Within multidisciplinary teams, statisticians and data scientists are increasingly involved in clinical trials that incorporate digital clinical measures. They are called upon to provide input into trial planning, generation of evidence on the clinical validity of novel clinical measures, and evaluation of the adequacy of existing evidence. Analysis objectives related to demonstrating clinical validity of novel clinical measures differ from typical objectives related to demonstrating safety and efficacy of therapeutic interventions using established measures which statisticians are most familiar with. Key Messages: This paper discusses key considerations for generating evidence for clinical validity through the lens of the type and intended use of a clinical measure. This paper also briefly discusses the regulatory pathways through which clinical validity evidence may be reviewed and highlights challenges that investigators may encounter while dealing with data from biometric monitoring technologies. © 2022 The Author(s). Published by S. Karger AG, Basel. This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC). Usage and distribution for commercial purposes requires written permission.