Human mistakes are still one of the main reasons of underlying regulatory affairs that in a compliance with FDA's Data Integrity and Analytical Quality by Design (AQbD) must be eliminated. To develop smooth, fast and robust methods that are free of human failures, a state-of-the-art automation was presented. For the scope of this study, a commercial software (DryLab) and a model mixture of 10 drugs were subjected to testing. Following AQbD-principles, the best available working point was selected and conformational experimental runs, i.e. the six worst cases of the conducted robustness calculation, were performed. Simulated results were found to be in excellent agreement with the experimental ones, proving the usefulness and effectiveness of an automated, software-assisted analytical method development.

HPLC method modeling is becoming a powerful tool to be used in the communication about method quality in HPLC between different labs, different companies, and between companies and regulatory agencies. The understanding of simple rules of peak movements will facilitate the development of new drugs, which are badly needed for smaller patient populations. The new features of HPLC modeling software, such as 3D resolution map, the modeled robustness testing, a practicable method transfer, or a method knowledge management offer a closed loop of all information about the birth and practical use of a method, and it further suggests the use of such software solutions in regulated laboratories to make analyst's life easier-especially in the pharmaceutical industry.

Modeling of HPLC methods using QbD principles in HPLC.

• Emphasizes the integration of chromatographic methods and sample preparation.
• Explains how liquid chromatography is used in different industrial sectors.
• Covers the most interesting and valuable applications in different fields, e.g., proteomic, metabolomics, foodomics, pollutants and contaminants, and drug analysis (forensic, toxicological, pharmaceutical, biomedical).
• Includes references and tables with commonly used data to facilitate research, practical work, comparison of results, and decision-making.

In the pharmaceutical industry, the analysis of atropisomers is of considerable interest from a scientific and regulatory perspective. The compound of interest contains two stereogenic axes due to the hindered rotation around the single bonds connecting the aryl groups, which results in four potential configurational isomers (atropisomers). The separation of the four atropisomers is achieved on a derivatized β-cyclodextrin bonded stationary phase. Further investigation shows that low temperature conditions, including sample preparation (−70 °C), sample storage (−70 °C), and chromatographic separation (6 °C), were critical to preventing interconversion. LC-UV-Laser Polarimetric analysis identified peak 1/2 as a pair of enantiomers and peak 3/4 as another. Thermodynamic analysis of the retention data indicated that the separation of the pairs of enantiomers is primarily enthalpy controlled as indicated by the positive slope of the van’t Huff plot. The difference in absolute Δ (Δ H), ranged from 2.20 kJ/mol to 2.42 kJ/mol.

The aim of this article is to illustrate the current status of computer-assisted method development and retention modelling. This study focuses on the successful method development of typical small pharmaceutical compounds (impurity profiling) and large therapeutic proteins. By choosing appropriate initial conditions, the method development can be performed in less than one day. However, for small molecules possessing different physicochemical properties, the conditions can be multifarious, while for biopharmaceuticals (for example, monoclonal antibodies [mAbs], antibody–drug conjugates [ADCs]), a generic method can easily be developed. In addition to retention modelling and optimization, the potential of simulated robustness testing is also demonstrated. Depending on the applied retention model, the impact of any change among six experimental parameters (t_G, T, pH, ternary composition, flow rate, and initial- and final mobile phase compositions) on the separation can be assessed using a 2⁶ or 3⁶ type virtual factorial design. No additional experiments are required to perform the robustness evaluation. Finally, virtual method transfer between different chromatographic systems is demonstrated.

This study reports the use of modelling software for the successful method development of IgG1 cysteine conjugated antibody drug conjugate (ADC) in RPLC. The goal of such a method is to be able to calculate the average drug to antibody ratio (DAR) of and ADC product. A generic method development strategy was proposed including the optimization of mobile phase temperature, gradient profile and mobile phase ternary composition. For the first time, a 3D retention modelling was presented for large therapeutic protein. Based on a limited number of preliminary experiments, a fast and efficient separation of the DAR species of a commercial ADC sample, namely brentuximab vedotin, was achieved. The prediction offered by the retention model was found to be highly reliable, with an average error of retention time prediction always lower than 0.5% using a 2D or 3D retention models. For routine purpose, four to six initial experiments were required to build the 2D retention models, while 12 experiments were recommended to create the 3D model. At the end, RPLC can therefore be considered as a good method for estimating the average DAR of an ADC, based on the observed peak area ratios of RPLC chromatogram of the reduced ADC sample.