Artificial Intelligence in Pharmaceutical Development: Accelerating Formulation, Screening, and Approval

Abstract

Artificial Intelligence (AI) has rapidly become the backbone of modern pharmaceutical research, revolutionizing every phase of drug development—from target identification and compound screening to formulation design, clinical trials, and regulatory review. Traditional pharmaceutical R&D, which typically requires 10–15 years and billions of dollars, is being reimagined through machine learning (ML), deep learning (DL), and data-driven automation. This review comprehensively explores the integration of AI in pharmaceutical formulation, high-throughput screening, predictive toxicology, pharmacokinetic modeling, and regulatory decision-making. It highlights current technologies, case studies of AI-driven drug approvals, ethical considerations, and the future outlook of fully autonomous drug discovery pipelines.