Remote Cardiac Safety Monitoring through the Lens of the FDA Biomarker Qualification Evidentiary Criteria Framework: A Case Study Analysis.

Biomarkers Cardiac Digital health Evidentiary criteria Remote monitoring Sensors

Journal

Digital biomarkers
ISSN: 2504-110X
Titre abrégé: Digit Biomark
Pays: Switzerland
ID NLM: 101707633

Informations de publication

Date de publication:
Historique:
received: 21 10 2020
accepted: 28 12 2020
entrez: 31 5 2021
pubmed: 1 6 2021
medline: 1 6 2021
Statut: epublish

Résumé

Clinical safety findings remain one of the reasons for attrition of drug candidates during clinical development. Cardiovascular liabilities are not consistently detected in early-stage clinical trials and often become apparent when drugs are administered chronically for extended periods of time. Vital sign data collection outside of the clinic offers an opportunity for deeper physiological characterization of drug candidates and earlier safety signal detection. A working group representing expertise from biopharmaceutical and technology sectors, US Food and Drug Administration (FDA) public-private partnerships, academia, and regulators discussed and presented a remote cardiac monitoring case study at the FNIH Biomarkers Consortium Remote Digital Monitoring for Medical Product Development workshop to examine applicability of the biomarker qualification evidentiary framework by the FDA. This use case examined the components of the framework, including the statement of need, the context of use, the state of the evidence, and the benefit/risk profile. Examination of results from 2 clinical trials deploying 510(k)-cleared devices for remote cardiac data collection demonstrated the need for analytical and clinical validity irrespectively of the regulatory status of a device of interest, emphasizing the importance of data collection method assessment in the context of intended use. Additionally, collection of large amounts of ambulatory data also highlighted the need for new statistical methods and contextual information to enable data interpretation. A wider adoption of this approach for drug development purposes will require collaborations across industry, academia, and regulatory agencies to establish methodologies and supportive data sets to enable data interpretation and decision-making.

Identifiants

pubmed: 34056520
doi: 10.1159/000515110
pii: dib-0005-0103
pmc: PMC8138142
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

103-113

Informations de copyright

Copyright © 2021 by S. Karger AG, Basel.

Déclaration de conflit d'intérêts

E.S.I. is an employee of Koneksa Health and may own company stock. B.W. is an advisor for Koneksa Health and Elektra Labs and received consulting fees from Teladoc and research funding from Pfizer. J.A.W. is an employee of Cygnal Therapeutics and may own company stock, and he is a member of the FNIH Biomarkers Consortium Executive Committee. All of the other authors have no conflict of interests. The mention of commercial products, their sources, or their use in connection with material reported herein is not to be construed as either an actual or an implied endorsement of such products by the Department of Health and Human Services. This article reflects the views of the author and should not be construed to represent views or policies of the FDA.

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Auteurs

Elena S Izmailova (ES)

Koneksa Health, New York, New York, USA.

William A Wood (WA)

Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA.

Qi Liu (Q)

Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research Food and Drug Administration, Silver Spring, Maryland, USA.

Vadim Zipunnikov (V)

Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

Daniel Bloomfield (D)

Anthos Therapeutics, Cambridge, Massachusetts, USA.

Jason Homsy (J)

Takeda Pharmaceuticals International, Cambridge, Massachusetts, USA.

Steven C Hoffmann (SC)

Foundation for the National Institutes of Health (NIH), North Bethesda, Maryland, USA.

John A Wagner (JA)

Cygnal Therapeutics, Cambridge, Massachusetts, USA.

Joseph P Menetski (JP)

Foundation for the National Institutes of Health (NIH), North Bethesda, Maryland, USA.

Classifications MeSH