Clinical trials are being rapidly transformed by artificial intelligence (AI), which improves the speed, precision, and efficiency of the drug development process. AI- driven solutions allow the analysis of large-scale datasets to enhance patient recruitment, optimize trial design, and produce more accurate outcome forecasts. Conventional clinical trials are frequently time-consuming, costly, and difficult. The development of customized medicine is aided by machine learning algorithms that use genomic data, electronic health records, and empirical evidence to forecast patient responses. AI also makes it easier to identify negative events early and enhances risk management techniques. Human error is decreased and overall trial quality is improved by automation and sophisticated data monitoring. Despite these benefits, issues including algorithmic bias, data privacy concerns, and regulatory obstacles need to be resolved. All things considered, AI has enormous potential to transform clinical trials, resulting in future drug development that is safer, quicker, and more economical.
1*Handal Sanskruti Dilip, 2Hake Asmita Hanumant, 3Chormale Gayatri Laxman, 4Maharnor Rutuja Balasaheb, 5Dr. Vikas L. Gadadhe, 6Miss. Anushka H. Hake (Fri,) studied this question.