Improvement of a stability-indicating method by Quality-by-Design versus Quality-by-Testing: a case of a learning process.

The understanding of the method is a major concern when developing a stability-indicating method and even more so when dealing with impurity assays from complex matrices. In the presented case study, a Quality-by-Design approach was applied in order to optimize a routinely used method. An analytical issue occurring at the last stage of a long-term stability study involving unexpected impurities perturbing the monitoring of characterized impurities needed to be resolved. A compliant Quality-by-Design (QbD) methodology based on a Design of Experiments (DoE) approach was evaluated within the framework of a Liquid Chromatography (LC) method. This approach allows the investigation of Critical Process Parameters (CPPs), which have an impact on Critical Quality Attributes (CQAs) and, consequently, on LC selectivity. Using polynomial regression response modeling as well as Monte Carlo simulations for error propagation, Design Space (DS) was computed in order to determine robust working conditions for the developed stability-indicating method. This QbD compliant development was conducted in two phases allowing the use of the Design Space knowledge acquired during the first phase to define the experimental domain of the second phase, which constitutes a learning process. The selected working condition was then fully validated using accuracy profiles based on statistical tolerance intervals in order to evaluate the reliability of the results generated by this LC/ESI-MS stability-indicating method. A comparison was made between the traditional Quality-by-Testing (QbT) approach and the QbD strategy, highlighting the benefit of this QbD strategy in the case of an unexpected impurities issue. On this basis, the advantages of a systematic use of the QbD methodology were discussed.