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Updated: Jul 14, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
How Digital Health Technologies have been Used to Support Regulatory Drug Approval
Agathe Thierry1,2, Antoine Manson3, Hans-Peter Podhaisky4
1Bayer AG, Research & Development, Pharmaceuticals, Regulatory Affairs, Berlin, Germany.
Objective:
The integration of Digital Health Technologies (DHTs) in clinical trials enhances patient recruitment, streamlines data collection, and provides new endpoints. However, a complex regulatory environment limits their adoption. This report reviews how DHTs have supported regulatory decision-making for drug marketing authorization in the US and Europe, detailing the types and purposes of DHTs utilized.
Methods:
Our analysis using Cortellis® examined drug approvals from September 2021 to March 2025, featuring a quantitative review of 60 DHT-related approvals and qualitative case studies.
Results:
Of the 60 approvals, 39 (63%) were granted by the EMA and 23 (37%) by the FDA. The predominant DHTs were ePRO tools (70%), with smartphones (66%) as the leading platform. Most DHTs were used in Phase 3 trials (82%) primarily for collecting safety and efficacy data. Notably, no approvals were based solely on DHT-derived primary endpoints. Case studies illustrate the tools' nature and highlight the importance of interaction with health authorities for successful implementation. An analysis of DHT use in clinical trials for investigational drugs on ClinicalTrials.gov showed five references where digital biomarkers were measured through DHTs, while no references for digital biomarkers were found in the approval reports.
Conclusion:
DHTs are regularly used by clinical trial sponsors and acknowledged by authorities for regulatory decision-making. Current approvals mainly involve ePRO tools with limited capabilities. The landscape is evolving; more sophisticated digital evidence generation tools are emerging, such as sensor-based DHTs (sDHT) and Artificial Intelligence/Machine Learning (AI/ML). Close collaboration between industry and regulators is vital for developing DHT qualification pathways.
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