A methodology employing retention modeling for achieving control space in liquid chromatography method development using quality by design approach

• Published in: Journal of Chromatography A 2021-01, Vol.1635, p.461658, Article 461658
• Main Authors: Jayaraman, Karthik, Rajendran, Ashok Kumar, Kumar, Gandhi Santosh, Bhutani, Hemant
• Format: Article
• Language: English
• Subjects: DryLab; In-silico optimization; Liquid chromatography method development; Quality by design; Retention modeling; Robustness evaluation
• ISSN: 0021-9673
• DOI: 10.1016/j.chroma.2020.461658

•Quality-by-design based liquid chromatographic method for new chemical entity.•Exploration of design space using 2D and 3D chromatographic retention modeling.•Establishment of a methodology for achieving analytical method control space.•Demonstration of dependence of method control space on control strategy.•Use of DryLabⓇ to evaluate method robustness with acceptable accuracy. This study reports the application of retention modeling and quality by design practices for reverse-phase liquid chromatographic method development of a new chemical entity. Prior to the retention modeling, preliminary screening experiments were performed for the selection of stationary phase, organic modifiers, and method parameters. Based on the results of preliminary method conditions, tG-T (gradient time - temperature) 2-D modeling with 4 input runs, and tG-T-tc (gradient time-temperature-ternary composition) 3-D modeling with 12 input runs were designed to build a model for achieving the optimized separation. Modeling of reverse phase separations was based on the measurement of both retention times and peak areas. A design space with appropriate input variables and control strategy was established prior to optimization and robustness evaluation following the quality by design framework. DryLabⓇ was used to predict the optimized gradient profile and separation temperature. The robustness evaluation was carried out using the multiple factors at a time approach and the control space was established. The interdependence of control space and the control strategy was demonstrated by evaluating method robustness using two levels of system suitability criteria. The predictive accuracy of the retention modeling was established through experimental verification of the in-silico predictions. The quality by design based method development approach demonstrated the in-silico optimization as an integral component of reverse-phase chromatographic method development to evaluate the interplay of factors such as organic modifiers, separation temperature and gradient time, which greatly integrated and enhanced method robustness during method development.