Applications of artificial intelligence in optimizing drug therapies for cancer patients: An umbrella review

Background and Aims: Artificial intelligence (AI) offers an advanced approach to managing pharmacological (drug) treatments for cancer patients. Optimizing treatment protocols represents a cost-effective and safe strategy for drug utilization. AI is beneficial for both drug development and patient safety, providing a foundation for appropriate medication adaptation and use. Therefore, this systematic umbrella review was conducted in ۲۰۲۴ to investigate the applications of AI in optimizing drug therapies for cancer patients. Methods: To synthesize existing evidence, a systematic umbrella review was performed, examining prior systematic reviews focused on pharmaceutical applications of AI in cancer. This review adhered to PRISMA guidelines. A comprehensive search was conducted across Scopus, PubMed, Embase, and Web of Science, spanning from database inception through March ۵, ۲۰۲۵. Google Scholar was employed as a supplementary resource for manual searches. Eligibility criteria were applied during screening of titles, abstracts, and full-text reports. The study protocol was prospectively registered in the PROSPERO database. Results: The most common applications of AI in pharmaceutical therapies for cancer patients are identification and drug discovery, drug design, formulation, testing of pharmaceutical dosage forms, optimizing the dose schedule for administration of drugs, predicting drug interactions and combination effects, matching patients with the optimal drug, predicting drug-target interactions, drug-repurposing, and generally optimizing treatment protocols. Conclusion: This systematic umbrella review explores the wide-ranging applications of AI in drug therapies for cancer patients. Also, this review provides an overview of various AI-based approaches for physicians and pharmacists, highlighting their benefits and drawbacks. Nevertheless, fully realizing the potential of this technology for cancer patients requires further research to improve drug development