Revolutionizing clinical trials: the role of AI in accelerating medical breakthroughs

Clinical trials are the essential assessment for safe, reliable, and effective drug development. Data-related limitations, extensive manual efforts, remote patient monitoring, and the complexity of traditional clinical trials on patients drive the application of Artificial Intelligence (AI) in medic...

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Veröffentlicht in:International journal of surgery (London, England) England), 2023-12, Vol.109 (12), p.4211-4220
Hauptverfasser: Chopra, Hitesh, Annu, Shin, Dong K, Munjal, Kavita, Priyanka, Dhama, Kuldeep, Emran, Talha B
Format: Artikel
Sprache:eng
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Zusammenfassung:Clinical trials are the essential assessment for safe, reliable, and effective drug development. Data-related limitations, extensive manual efforts, remote patient monitoring, and the complexity of traditional clinical trials on patients drive the application of Artificial Intelligence (AI) in medical and healthcare organisations. For expeditious and streamlined clinical trials, a personalised AI solution is the best utilisation. AI provides broad utility options through structured, standardised, and digitally driven elements in medical research. The clinical trials are a time-consuming process with patient recruitment, enrolment, frequent monitoring, and medical adherence and retention. With an AI-powered tool, the automated data can be generated and managed for the trial lifecycle with all the records of the medical history of the patient as patient-centric AI. AI can intelligently interpret the data, feed downstream systems, and automatically fill out the required analysis report. This article explains how AI has revolutionised innovative ways of collecting data, biosimulation, and early disease diagnosis for clinical trials and overcomes the challenges more precisely through cost and time reduction, improved efficiency, and improved drug development research with less need for rework. The future implications of AI to accelerate clinical trials are important in medical research because of its fast output and overall utility.
ISSN:1743-9159
1743-9191
1743-9159
DOI:10.1097/JS9.0000000000000705