Recent Advances in Bioanalytical Method Development: Innovations in Analytical Techniques, Experimental Design, and Artificial Intelligence Applications

Abstract

Bioanalysis is a cornerstone of pharmaceutical research, enabling the quantitative determination of drugs, metabolites, and biomarkers in biological matrices. With increasing complexity in drug molecules and evolving regulatory expectations, advanced analytical techniques such as liquid chromatography–tandem mass spectrometry (LC-MS/MS) have become indispensable. In parallel, systematic statistical approaches, particularly design of experiments (DoE), are increasingly applied to optimize analytical workflows by enhancing efficiency, robustness,
and method reliability. This review provides a comprehensive overview of bioanalytical method development, with a primary focus on LC-MS/MS applications, method validation strategies, and DoE-based optimization. Key aspects such as sensitivity, selectivity, matrix effects, and reproducibility are critically discussed in the context of modern analytical requirements. The application of multivariate experimental design in identifying critical method parameters and establishing robust operating conditions is highlighted. In addition, recent advancements in data- driven analytical approaches and automated data processing are briefly discussed as emerging supportive tools in method development. Overall, the integration of advanced analytical techniques with structured experimental
design represents a significant step toward more efficient, reliable, and reproducible bioanalytical methods. Future perspectives emphasize the importance of regulatory alignment and the continued evolution of systematic approaches in analytical science.