• Pokharkar Pramod
• Darekar Vaibhav
• Pawade Omkar
• Shinde Saurabh
• Prof. Gadge Shubham

Clinical trials are the cornerstone of drug development, but their high cost and slow pace hinder medical progress. Artificial intelligence (AI) has emerged as a powerful tool to address these challenges. This review explores the current landscape of AI-powered clinical trial design and optimization. We examine how AI can be leveraged to streamline patient selection through improved inclusion/exclusion criteria and identification of optimal patient populations. Furthermore, AI's ability to analyze vast datasets allows for simulation of trials, prediction of patient outcomes, and selection of the most informative dosages and endpoints. These advancements hold promise for reducing trial size, minimizing patient burden, and ultimately accelerating the development of life-saving therapies.

Artificial intelligence, Machine learning, Clinical trial design, Clinical trial, optimization.

"AI-powered Clinical Trial Design and Optimization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.i98-i102, May-2024, Available :http://www.jetir.org/papers/JETIR2405813.pdf

"AI-powered Clinical Trial Design and Optimization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppi98-i102, May-2024, Available at : http://www.jetir.org/papers/JETIR2405813.pdf