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Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials.
Ratitch, Bohdana; Rodriguez-Chavez, Isaac R; Dabral, Abhishek; Fontanari, Adriano; Vega, Julio; Onorati, Francesco; Vandendriessche, Benjamin; Morton, Stuart; Damestani, Yasaman.
Afiliação
  • Ratitch B; Statistics and Data Insights, Bayer, Westmount, Québec, Canada.
  • Rodriguez-Chavez IR; Strategy Center for Decentralized Clinical Trials and Digital Medicine, Drug Development Solutions, ICON plc, Blue Bell, Pennsylvania, USA.
  • Dabral A; Global Development Operations, Amgen Inc., Thousand Oaks, California, USA.
  • Fontanari A; Product, PatchAi S.r.l., an Alira Health Company, Padua, Italy.
  • Vega J; Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Onorati F; Applied Data Science, Current Health, A Best Buy Health Company, Boston, Massachusetts, USA.
  • Vandendriessche B; Byteflies, Antwerp, Belgium & Department of Electrical, Computer and Systems Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
  • Morton S; Emerging Digital Medicines, Eli Lilly & Co., Indianapolis, Indiana, USA.
  • Damestani Y; Digital Medicine, Karyopharm Therapeutics, Newton, Massachusetts, USA.
Digit Biomark ; 6(3): 83-97, 2022.
Article em En | MEDLINE | ID: mdl-36466953
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article