Author(s):
Rohit P. Mane, Priya N. Shendage, Priyanka S. Jadhav, Rutuja A. Patil
Email(s):
priyankajadhav55055@gmail.com
DOI:
10.52711/0975-4377.2026.00021 
Address:
Rohit P. Mane, Priya N. Shendage, Priyanka S. Jadhav*, Rutuja A. Patil
Department of Pharmaceutics, Shree Santkrupa College of Pharmacy, Ghogaon-karad, Maharashtra 41511.
*Corresponding Author
Published In:
Volume - 18,
Issue - 2,
Year - 2026
ABSTRACT:
Artificial Intelligence (AI) is revolutionizing pharmacy across drug discovery, formulation, clinical practice, and supply chain management. Techniques like machine learning, deep learning, natural language processing, and graph-based models enable efficient target identification, ADMET (absorption, distribution, metabolism, excretion, toxicity) prediction, formulation optimization, and automation of routine tasks, freeing pharmacists for patient-focused care. Key applications include virtual screening and de novo drug design, which halve hit-to-lead timelines; AI-driven manufacturing for real-time process monitoring and yield optimization; robotic dispensing reducing errors to near-zero; and clinical decision support systems predicting adverse drug reactions and interactions. Personalized pharmacy leverages genetic and monitoring data for precise dosing, while patient engagement tools like chatbots boost adherence. Ethical challenges are prominent, including data privacy under HIPAA/GDPR, algorithmic bias risking healthcare disparities, lack of transparency in "black-box" models, and accountability for AI errors. Mitigation strategies involve diverse datasets, explainable AI (XAI), encryption, fairness audits, regulatory clarity, and mandatory human oversight by pharmacists. Measurable impacts show 20-33% productivity gains, faster drug discovery, and bias detection needs. An implementation roadmap starts with pilots in low-risk areas like inventory forecasting, followed by data governance, validation, oversight boards, and AI literacy training. This integration promises enhanced efficiency and safety but demands balanced governance to avoid risks like skill erosion or inequalities.
Cite this article:
Rohit P. Mane, Priya N. Shendage, Priyanka S. Jadhav, Rutuja A. Patil. AI and the Future of Pharmacy: Innovation, Ethics, and Impact. Research Journal of Pharmaceutical Dosage Forms and Technology. 2026; 18(2):137-0. doi: 10.52711/0975-4377.2026.00021
Cite(Electronic):
Rohit P. Mane, Priya N. Shendage, Priyanka S. Jadhav, Rutuja A. Patil. AI and the Future of Pharmacy: Innovation, Ethics, and Impact. Research Journal of Pharmaceutical Dosage Forms and Technology. 2026; 18(2):137-0. doi: 10.52711/0975-4377.2026.00021 Available on: https://www.rjpdft.com/AbstractView.aspx?PID=2026-18-2-7
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