Role of Artificial Intelligence in Analytical Method Development

Abstract

Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), is reshaping analytical method development by enabling data-driven, automated, and predictive workflows. In pharmaceutical, environmental, and industrial laboratories, AI accelerates chromatographic and spectrometric method optimization, improves peak detection and quantification, supports impurity profiling and stability-indicating methods, and facilitates regulatory-compliant process analytical technology (PAT). This article reviews the role of AI across the analytical method lifecycle—from method design and optimization to validation and lifecycle management—and discusses key algorithms, case studies, regulatory aspects, limitations, and future directions.