Evaluating the Impact of Artificial Intelligence on Vaccine Development: A Systematic Review of Lessons Learned from the Covid-19 Pandemic
Abstract:
The integration of artificial intelligence (AI) into vaccine development has transformed the field, particularly during the COVID-19 pandemic. This systematic review critically examines the role of AI in expediting the identification of vaccine candidates, optimizing clinical trial designs, and overcoming logistical challenges associated with global distribution. We conducted a comprehensive literature search across multiple databases, including PubMed and Web of Science, adhering to PRISMA guidelines to evaluate peer-reviewed studies on AI-driven vaccine development. Key case studies, such as the Pfizer-BioNTech and Moderna vaccines, demonstrate how AI-driven machine learning algorithms significantly shortened traditional vaccine development timelines from years to months, while maintaining safety and efficacy standards. Our synthesis reveals that AI facilitated real-time monitoring of clinical trial data, optimizing patient stratification and dynamically addressing adverse events. Furthermore, AI-powered models improved vaccine distribution strategies, addressing logistical challenges such as cold-chain management. Ethical and technical challenges, including algorithmic biases and data privacy concerns, were identified and discussed. This review highlights the transformative potential of AI in accelerating future vaccine development and pandemic preparedness. Continued interdisciplinary collaboration between AI experts, immunologists, and public health authorities will be critical for shaping the future of vaccine innovation.
