Artificial Intelligence Based in silico Clinical Trials for Vaccines

This paper explores the transformative potential of Artificial Intelligence (AI) in enabling in silico clinical trials (ISCTs) for vaccine development. ISCTs, which simulate clinical trials using virtual patient cohorts, offer a cost-effective, ethical, and efficient alternative to traditional methods. AI significantly enhances ISCTs by automating trial design, optimizing patient selection, and simulating immune responses with unprecedented accuracy and scale. Applications include antigen discovery, vaccine formulation, efficacy and safety prediction, and personalized immunization strategies. Through a review of current research, tools, and industry practices, the paper illustrates how AI-driven ISCTs can reduce time-to-market, lower costs, improve trial diversity, and meet regulatory expectations. Despite challenges such as model validation, data bias, and regulatory uncertainties, AI-integrated ISCTs are positioned to revolutionize vaccine R&D. The paper concludes by highlighting future trends, including the integration of AI with emerging technologies, development of universal and personalized vaccines, and evolving regulatory frameworks to support these innovations.