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Data-Driven Approaches in Pharmaceutical Formulation and Drug Development: Case Studies and Insights



Sarhan E M ; Akhavan M
Authors

Source: Data-Driven Pharmaceutical Processing and Drug Development Published:2026

Abstract

The advent of artificial intelligence (AI) and data analytics has revolutionized the pharmaceutical pipeline of industrial development. They can enhance high-throughput drug design, optimize formulations, and streamline clinical trials in a much more accurate and efficient way with significantly reduced time and cost consumption. This chapter highlights the impact and challenges of integrated AI-driven strategies in the pharmaceutical industry. Case studies are implied to explore in-depth evaluation of integrated machine learning (ML) automation, predictive modeling, mathematical algorithms, and big data analytics in enhancing drug discovery, formulations, and personalized medicine. The chapter also addresses the challenges, ethical and data privacy considerations, policies of AI integration, and future trends in leveraging data for innovative drug discovery and development. © 2026 by John Wiley & Sons Ltd.