Artificial Intelligence in Medical Prescription: Revolution, Risks and Future Aspects
Shital Chaudhari1★, Tularam Barot1★ Corresponding author
- 1Department of Pharmaceutical Technology, Parul Institute of Pharmacy and Research, Parul University, Vadodara, Gujarat, INDIA.
CORRESPONDENCE
Shital Chaudhari
Department of Pharmaceutical Technology, Parul Institute of Pharmacy and Research, Parul University, Vadodara, Gujarat, INDIA.
Received: 11-09-2025; Revised: 29-10-2025; Accepted: 02-12-2025.
Volume 14, Issue 3 · pp. 541–546 · PUBLISHED · DOI: 10.5530/ajbls.20250039
ABSTRACT
The integration of Artificial Intelligence (AI) into medical prescription systems has transformed modern medicine. With tools such as DrugGPT and Clinical Decision Support Systems (CDSS), AI helps clinicians evaluate patient data more effectively, select medications, and prevent medication errors. This review examines the current landscape of AI-driven prescribing, highlighting benefits like increased efficiency, accuracy, cost savings, and greater accessibility of prescriptions. It also discusses important advancements such as machine learning, natural language processing, and Retrieval-Augmented Generation (RAG), each contributing to better, insight-driven healthcare decisions. However, using AI also entails certain risks. We must carefully address issues like data privacy, ensure transparency in AI operations, prevent unfair biases, and maintain accountability. Most importantly, we must protect and nurture human empathy within our healthcare system. Achieving this requires thoughtful regulatory frameworks such as the European Union AI Act, the Health Insurance Portability and Accountability Act, and India’s Digital Personal Data Protection Act. A hybrid approach combining human oversight with AI efficiency appears to be the safest and most sustainable path forward. The future of AI in prescribing involves federated learning, human-in-the-loop systems, and expanded use in underserved regions, ensuring ethical, secure AI-powered healthcare and safeguarding individuals.
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Chaudhari, S., & Barot, T. (). Artificial Intelligence in Medical Prescription: Revolution, Risks and Future Aspects. Asian Journal of Biological and Life sciences, 14(3), 541–546. https://doi.org/10.5530/ajbls.20250039