Sep 2026· Drug Metabolism and Bioanalysis· 0 citations
TL;DR
This review provides a thorough investigation into the design and validation of bioanalytical techniques utilizing the AQbD framework, in accordance with ICH rules that delineate GLP and controlled bioanalysis.
Abstract
Bioanalysis is essential in current drug discovery and development
research for the healthcare industry. Bioanalysis involves the assessment of analytes, such as
medicines, metabolites, and biomarkers, in biological specimens.
This method includes several stages, from sample collection to analysis and subsequent
data reporting. The first phase is to gather samples from clinical or preclinical trials, which
are then sent to the laboratory for faster analysis. The second step entails sample clean-up, or
sample preparation, which is deemed an essential aspect of bioanalysis.
Liquid Chromatography-Tandem Mass Spectrometry (LC–MS/MS) is the most favored
technique for separation and detection in bioanalytical laboratories. This stems from the enhanced
selectivity and sensitivity of other vital techniques, such as LC-NMR, GC-MS, GC-IR,
CE-MS, and GC-NMR, which enable precise and rapid analysis of complex sample mixtures,
offering improved reproducibility and greater automation.
Moreover, comprehending the analyte's chemical structure and characteristics is
crucial before initiating bioanalytical procedures. This review provides a thorough investigation
into the design and validation of bioanalytical techniques utilizing the AQbD framework, in
accordance with ICH rules that delineate GLP and controlled bioanalysis.
This review also provides a comprehensive overview of the above-reported hyphenated
techniques, employing Statistical Quality Control (SQC) monitoring and regulatory compliance
using an advanced AQbD approach, highlighting their current status and future directions.
This critical review comprehensively evaluates the current state of pharmaceutical bioanalysis by examining emerging LC-MS technologies, sustainable analytical strategies, and the growing role of artificial intelligence (AI) and machine learning (ML) in analytical optimization, spectral interpretation, biomarker discov...
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