Evidence map›Paper›PMID 37901363›Full record

ArticleDigital biomarkers

Regulatory Qualification of a Cross-Disease Digital Measure: Benefits and Challenges from the Perspective of IMI Consortium IDEA-FAST.

David Nobbs, Wojciech Piwko, Christopher Bull, Francesca Cormack, Teemu Ahmaniemi, Sebastian C Holst, Meenakshi Chatterjee, Walter Maetzler, Stefan Avey, Wan Fai Ng and 1 more

Abstract read
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Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

11 authors.

David NobbsRoche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Wojciech PiwkoTakeda Pharmaceuticals International, Zurich, Switzerland.
Christopher BullOpen Lab, School of Computing, Newcastle University, Newcastle upon Tyne, UK.
Francesca CormackCambridge Cognition, Cambridge, UK.
Teemu AhmaniemiVTT Technical Research Center of Finland Ltd., Espoo, Finland.
Sebastian C HolstRoche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Meenakshi ChatterjeeJanssen Research and Development, Cambridge, MA, USA.
Walter MaetzlerDepartment of Neurology, University Hospital Schleswig-Holstein and Kiel University, Kiel, Germany.
Stefan AveyJanssen Research and Development, Spring House, PA, USA.
Wan Fai NgTranslational and Clinical Research Institute, Newcastle University and NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.
IDEA-FAST Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Innovative Medicines Initiative (IMI) consortium IDEA-FAST is developing novel digital measures of fatigue, sleep quality, and impact of sleep disturbances for neurodegenerative diseases and immune-mediated inflammatory diseases. In 2022, the consortium met with the European Medicines Agency (EMA) to receive advice on its plans for regulatory qualification of the measures. This viewpoint reviews the IDEA-FAST perspective on developing digital measures for multiple diseases and the advice provided by the EMA. Summary: The EMA considered a cross-disease measure an interesting and arguably feasible concept. Developers should account for the need for a strong rationale that the clinical features to be measured are similar across diseases. In addition, they may expect increased complexity of study design, challenges when managing differences within and between disease populations, and the need for validation in both heterogeneous and homogeneous populations. Key Messages: EMA highlighted the challenges teams may encounter when developing a cross-disease measure, though benefits potentially include reduced resources for the technology developer and health authority, faster access to innovation across different therapeutic fields, and feasibility of cross-disease comparisons. The insights included here can be used by project teams to guide them in the development of cross-disease digital measures intended for regulatory qualification.

Indexed as

Digital evidenceRegulatory scienceWearables

Identifiers

PMID37901363
PMCPMC10601930

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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.