Applications of Artificial Intelligence in High-Performance Liquid Chromatography: A Scoping Review

Objective: This scoping review aims to map the existing literature on the applications of artificial intelligence techniques in liquid chromatography, encompassing the prediction of chromatographic responses, method development, data processing, quality control, and automation. Inclusion criteria: This review will include peer-reviewed primary studies involving Liquid chromatography that employ AI-based models on some part of the chromatographic work streamline. Studies may involve method development, validation, or proof-of-concept experiments. No date or language restrictions will be applied, provided the text is written in Roman characters. Methods: This review follows the JBI methodology for scoping reviews. Search strategies will be conducted in Web of Science, Scopus, and PubMed. Citations will be managed using Systematic Review Accelerator and Rayyan. Two reviewers will independently perform study selection and data extraction. Results will be presented in tables, diagrams, and graphs to highlight patterns, methodologies, and research gaps.