Evidence map›Paper›PMID 34056520›Full record

ReviewDigital biomarkers

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

Elena S Izmailova, William A Wood, Qi Liu, Vadim Zipunnikov, Daniel Bloomfield, Jason Homsy, Steven C Hoffmann, John A Wagner, Joseph P Menetski

Abstract readReview
In one paragraph

Review in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Elena S IzmailovaKoneksa Health, New York, New York, USA.
William A WoodLineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA.
Qi LiuOffice of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research Food and Drug Administration, Silver Spring, Maryland, USA.
Vadim ZipunnikovJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Daniel BloomfieldAnthos Therapeutics, Cambridge, Massachusetts, USA.
Jason HomsyTakeda Pharmaceuticals International, Cambridge, Massachusetts, USA.
Steven C HoffmannFoundation for the National Institutes of Health (NIH), North Bethesda, Maryland, USA.
John A WagnerCygnal Therapeutics, Cambridge, Massachusetts, USA.
Joseph P MenetskiFoundation for the National Institutes of Health (NIH), North Bethesda, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

BiomarkersCardiacDigital healthEvidentiary criteriaRemote monitoringSensors

Identifiers

PMID34056520
PMCPMC8138142

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.