Artificial Intelligence and Machine Learning for Pharmacy Students and Pharmaceutical Professionals: a Narrative Review

Abstract

 Artificial intelligence (AI) and machine learning (ML) are computer science fields that develop systems capable of learning from data, recognizing patterns and making decisions without explicit programming. They are valuable tools for assisting in student learning, the pharmaceutical industry, drug discovery, clinical trials, etc. Therefore, this review aimed to discuss the application of AI/ML in pharmacy education and pharmaceutical professions. We retrieved articles from online databases such as EMBASE, PubMed, and Google Scholar by using some common terms like "AI/ML," "Pharmacy education/profession," "Pharmaceutical sciences/industry," "Drug design/development," etc. Innovative strategies for teaching and learning are offered by AI/ML, making educational content more accessible. They generate practice questions for self-assessment and exam readiness, aligning with lecture content and case-based approaches in pharmacy. Pharmaceutical professionals can use AI tools in drug discovery and development to propose novel drug-like structures, optimize drug candidates based on efficacy, safety and pharmacokinetics, and predict drug properties using preclinical and clinical data. These tools help to find potential risks early in the development process, allowing for proactive modifications and optimization of drug performance. They can develop a suitable formulation and select an appropriate dosage form for a new drug molecule as well as help determine the nature, quantity and type of pharmaceutical excipient. AI systems can guide manufacturing processes by analyzing preliminary information from batches and converting results into guidelines. They can develop advanced marketing strategies and streamline pharmaceutical supply chains, ensuring efficient manufacturing and inventory management. AI technologies have the ability to revolutionize hospital pharmacy and community pharmacy by providing real-time updates on medications, potential drug interactions, medication errors and adverse reactions and dosage recommendations to ensure patient safety and therapeutic effectiveness. They can significantly boost pharmacy profitability by predicting medication demand, optimizing inventory management, and improving operational efficiency. The most common AI tools used by pharmacy students and pharmaceutical professionals are ChatGPT, Quilobolt, Wolfram, MEDi, AlphaFold, Toxtree, LimTox, ANN, IBM Watson, CASTER, etc.

Bangladesh Pharmaceutical Journal 28(2): 228-239, 2025 (July)