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.