The recent literature emphasizes significant advancements in drug discovery and clinical trial methodologies, notably through the integration of artificial intelligence (AI) and machine learning. Key studies highlighted include a review of drug approval trends in China and emerging multi-omics technologies for drug discovery. Advanced tools like large language models are increasingly employed to enhance clinical trial efficiency and participant matching. Challenges such as recruitment barriers and informed consent processes are being addressed with innovative approaches, including AI-driven strategies. Furthermore, ethical concerns surrounding AI usage in healthcare and the importance of regulatory frameworks have been discussed extensively. Articles also underline how automated data extraction and natural language processing improve clinical decision-making and patient outcomes. Overall, the intersection of AI with clinical trial frameworks presents exciting opportunities while also necessitating careful examination of ethical and operational implications in the evolving landscape of healthcare.
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Harnessing Large Language Models in Clinical Trials: Innovations, Applications, and Future Prospects | BMC Medicine
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