NeuralCipher Research overview
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Pharmacology remains a cognitively demanding discipline for medical students due to its volume and integration of complex pathophysiological principles. Educational podcasts have emerged as accessible, asynchronous learning resources in health professions education. With recent advances in artificial intelligence (AI), automated guided-content generation provides new avenues for educational innovation. This study evaluates the feasibility, utilization, and learner reception of AI-generated pharmacology podcasts in undergraduate medical education at a US osteopathic medical school. In a retrospective observational study, pharmacology lectures across four organ system-based courses were converted into AI-generated podcast episodes using the NotebookLM and Riverside.fm platforms. Podcasts were made available via the Leo Learning Management System. Download metrics, presence of embedded practice questions, and qualitative student feedback were analyzed. Ten AI-generated podcasts were deployed across first- and second-year osteopathic medical courses. The average duration of the podcasts was 18.1 min. The range for AI podcast downloads was 6-25% whereas it was 50-97% for lecture slides and 1-9% for recommended pharmacology textbooks. Topics such as gastrointestinal pharmacology and Parkinson disease had the highest engagement. Podcasts with integrated practice questions showed slightly increased engagement. Students valued the format for its portability, clarity, and reinforcement of lecture content. AI-generated podcasts represent a scalable, portable, and positively received modality for pharmacology instruction. This study demonstrates early feasibility and acceptance of AI tools in augmenting traditional didactics. Further research is needed to assess impacts on learning outcomes and long-term retention.
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