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

Autor: Chopra H; Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai - 602105, Tamil Nadu, India., Annu; Thin Film and Materials Laboratory, School of Mechanical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea., Shin DK; Thin Film and Materials Laboratory, School of Mechanical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea., Munjal K; Department of Pharmacy, Amity Institute of Pharmacy, Amity University, Noida, Uttar Pradesh 201303, India., Priyanka; Department of Veterinary Microbiology, College of Veterinary Science, Guru Angad Dev Veterinary and Animal Sciences University (GADVASU), Rampura Phul, Bathinda, Punjab., Dhama K; Indian Veterinary Research Institute (IVRI), Izatnagar, Bareilly, Uttar Pradesh., Emran TB; Department of Pharmacy, BGC Trust University Bangladesh, Chittagong.; Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International niversity, Dhaka, Bangladesh.
Jazyk: angličtina
Zdroj: International journal of surgery (London, England) [Int J Surg] 2023 Dec 01; Vol. 109 (12), pp. 4211-4220. Date of Electronic Publication: 2023 Dec 01.
DOI: 10.1097/JS9.0000000000000705
Abstrakt: 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.
(Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)
Databáze: MEDLINE
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