Generative AI in Medical Pharmacology: Balancing Educational Benefits and Hallucination Risks

Background: Generative Artificial Intelligence (AI), particularly large language models like ChatGPT, has rapidly entered medical education. In pharmacology instruction within MBBS programs, these AI tools offer novel educational benefitsfrom ondemand tutoring to personalized learningbut also pose risks due to "hallucinations, " i. e., AI -generated misinformation. Objective: This review explores how generative AI is being integrated into pharmacology education, the educational advantages it provides, the nature and causes of AI hallucinations, and the potential risks of relying on inaccurate AI -generated content in medical learning. Mitigation strategies, best practices, case examples, ethical considerations, and future directions are discussed to inform balanced and safe use. Methods: A literature review was conducted focusing on recent (2020-2025) peer -reviewed sources and authoritative reports on generative AI in medical and pharmacology education. Results: Generative AI can enhance pharmacology education through adaptive learning, rapid information access, and interactive simulations, which students have found useful for studying and clinical preparation. However, AI hallucinationsplausible -sounding yet incorrect answersare common, with studies reporting a substantial fraction of AI -generated medical responses containing errors. These inaccuracies can mislead learners and threaten patient safety if not recognized. Strategies such as careful validation of AI -provided information, AI literacy training, and technical approaches (e. g. retrieval -augmented generation) are identified to mitigate risks. Conclusions: Generative AI holds significant promise in medical pharmacology education by augmenting learning and engagement. Yet, educators and students must remain vigilant about AI hallucinations. A balanced approachleveraging AI's benefits while implementing safeguards and ethical guidelinesis essential to ensure that AI becomes a reliable adjunct in pharmacology education rather than a source of misinformation. Ongoing research, policy development, and training are needed to fully realize generative AI's potential in medical education while minimizing its risks.