ARTIFICIAL INTELLIGENCE AND PYTHON PROGRAMMING IN UNDERGRADUATE PHARMACY EDUCATION: ADVANTAGES, CHALLENGES FOR TEACHERS AND STUDENTS, AND SUGGESTIONS FOR EFFECTIVE IMPLEMENTATION

Vikash Agnihotri, Ankur Patel, Tapan Kumar Mahato*

ABSTRACT

The proposed subject Artificial Intelligence (AI) & Python Programming for Pharmacy – I represent a pioneering addition to the Bachelor of Pharmacy curriculum as envisioned by the Pharmacy Council of India (PCI). This course equips pharmacy graduates with the essential foundations of AI, machine learning (ML), and Python programming, enabling them to operate effectively in data-driven and technology-enabled pharmaceutical environments. Beginning with Unit 1, students explore the history, key approaches, and knowledge-representation methods of AI, gaining a conceptual grounding in symbolic, statistical, and connectionist paradigms. Unit 2 introduces core ML paradigms, supervised, unsupervised, and reinforcement learning, along with representative algorithms such as Naïve Bayes, k-Nearest Neighbours, regression models, clustering methods, and basic neural networks, fostering analytical problem-solving. Unit 3 contextualizes these approaches within pharmaceutical sciences, highlighting applications in drug discovery, formulation, quality assurance, pharmacovigilance, and regulatory science. Units 4 and 5 progressively train students in Python, from installation, syntax, and data types to advanced programming constructs, data handling, functions, file management, and exception handling. By integrating AI/ML theory with Python programming, students are prepared to analyze pharmaceutical case studies, implement small coding exercises, and develop mini-projects relevant to real-world challenges in formulation, manufacturing, and patient care. The course uniquely addresses both technical and domain-specific requirements through pharmacy-centered examples, ensuring relevance and engagement. With its forward-looking vision, this subject positions B.Pharm graduates for leadership roles in computational drug discovery, precision medicine, and intelligent pharmaceutical systems, aligning education with the evolving demands of healthcare and industry.

Keywords: Artificial Intelligence (AI), Machine Learning (ML), Python Programming, Pharmaceutical Applications, Drug Discovery and Development, Precision Medicine.