ArticleDigital health
Bridging policy and practice in smart clinical trials: Quantifying regulatory friction and technology adoption in Korea and the UK.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
2 authors.
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Abstract
Objective: Smart clinical trials integrating artificial intelligence (AI), wearable and Internet of Things (IoT) sensors, and data-driven platforms have the potential to make clinical research more efficient, inclusive, and patient-centered. However, regulatory permissiveness does not always translate into actual adoption in the real-world. This study aims to examine how national policy environments and operational factors interact to shape the uptake of digital trial technologies in Korea and the United Kingdom between 2015 and 2025. Methods: We analyzed 1172 interventional trials registered on ClinicalTrials.gov using a multi-label classification pipeline to identify the use of AI, wearable/IoT technologies, clinical data integration, and digital platforms. Adoption patterns were linked to a policy friction index that quantified seven categories of regulatory barriers in each country. Cross-country comparisons were conducted to assess alignment between policy permissiveness and observed technology adoption. Results: Despite relatively high policy openness, the United Kingdom demonstrated persistently low adoption of AI, wearable/IoT, and digital platform technologies, reflecting implementation barriers such as validation burden, governance requirements, and workflow integration challenges. In contrast, Korea exhibited strong uptake of clinical data integration technologies despite higher regulatory friction, driven by institutional data infrastructures and hospital-centric ecosystems. Overall, adoption patterns diverged systematically from policy expectations in both countries. Conclusions: These findings suggest that digital transformation in clinical research requires more than permissive policy frameworks; it depends on effective alignment among regulation, infrastructure, and implementation science. By introducing a reproducible framework that links regulatory friction to observed technology adoption, this study provides actionable insights for accelerating safe, interoperable, and scalable smart clinical trial deployment within evolving digital health ecosystems.
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