ArticleScientific reports2026
Navigating the EMA qualification of novel methodologies for digital endpoints: lessons from the DEEP project proof of concept.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As digital measures continue to transform drug development, clinical practice, and patient experience, there is an increasing need for standardization in the development, validation, qualification, and regulatory acceptance of these measures. A multi-stakeholder project, led by the Digital Evidence Ecosystem & Protocols (DEEP), in collaboration with EFPIA (European Federation of Pharmaceutical Industries and Associations) and the EMA (European Medicines Agency) was initiated to explore whether the DEEP platform could foster and facilitate regulatory qualification of digital measures in several ways: e.g.: pre-competitive collaboration for evidence generation, structured presentation of evidence to support qualification requests and explore utility with a view to lifecycle management of qualified measures, as well as the utility of the DEEP platform to potentially facilitate aspects of the EMA Qualification of Novel Methodologies. Working with stakeholders from eight pharmaceutical companies, a real-life use case was explored to investigate the potential of the DEEP platform and Stack Model for procedural and life-cycle management. The proof of concept supported the DEEP stack model’s utility to support regulatory review and acceptance of novel endpoints through standardization, data reusability, and structured approach to validation of digital endpoints. This paper presents the methodology used to conduct the proof of concept in a structured approach, as well as the results and learnings and can serve as a basis for how to structure other explorations with regulatory authorities, following principles of agility.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.