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AI and innovation in clinical trials
3
Zitationen
5
Autoren
2025
Jahr
Abstract
Clinical trials face persistent challenges in cost, enrollment, and generalizability. This perspective examines how artificial intelligence (AI), large language models (LLMs), adaptive trial designs, and digital twins (DTs) can modernize trial design and execution. We detail AI-driven eligibility optimization, reinforcement learning for real-time adaptation, and in silico DT modeling. Methodological, regulatory, and ethical hurdles are addressed, emphasizing the need for validated, scalable frameworks to enable responsible and widespread integration.
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Autoren
Institutionen
- University of California, Berkeley(US)
- Universidade de São Paulo(BR)
- Queen's University(CA)
- Kingston General Hospital(CA)
- German Cancer Research Center(DE)
- Heidelberg University(DE)
- University Hospital Bonn(DE)
- The University of Texas MD Anderson Cancer Center(US)
- Penn State Milton S. Hershey Medical Center(US)