Pharmaceutical bioanalysis plays a central role in drug development, therapeutic drug monitoring, pharmacokinetics, metabolomics, and clinical diagnostics; however, the increasing complexity of biological and pharmaceutical matrices has created major analytical challenges related to matrix effects and analyte instability. Endogenous compounds such as phospholipids, proteins, salts, metabolites, and formulation excipients can interfere with chromatographic separation and electrospray ionization, leading to ion suppression or enhancement, signal fluctuations, reduced sensitivity, and compromised quantitative accuracy. In addition, hydrolysis, oxidation, photodegradation, enzymatic degradation, and adsorption processes can significantly affect analyte stability during sample collection, storage, preparation, and LC-MS analysis. This review critically evaluates the mechanistic basis of matrix effects and analytical instability in pharmaceutical bioanalysis and highlights recent advances in intelligent analytical technologies designed to improve analytical robustness, reproducibility, and sustainability. Advanced sample preparation strategies, including selective SPE, phospholipid-removal systems, MIP, and microextraction technologies, together with modern LC-MS platforms such as UHPLC-MS/MS and HRMS, have significantly enhanced trace-level pharmaceutical analysis in complex matrices. Furthermore, artificial intelligence-assisted workflows, microfluidics, biosensors, and omics-based analytical systems are transforming pharmaceutical bioanalysis toward automated and smart analytical ecosystems. Future pharmaceutical bioanalysis is expected to integrate intelligent, sustainable, and highly automated analytical systems that combine AI-driven analytics, advanced LC-MS technologies, green and white analytical chemistry principles, and harmonized regulatory frameworks to improve clinical applicability, analytical reliability, and environmental sustainability.
Barzani et al. (2026) studied this question.