The application of Quality-by-Design approaches in the development of analytical methods has changed the way drugs are manufactured, switching from trial-and-error and one-variable-at-a-time methods to a structured, risk-based scientific framework. The Analytical Target Profile is at the heart of Quality-by-Design. It clearly lays out the criteria for how well the method will perform. The identification of Critical Quality Attributes and Critical Method Parameters through systematic risk assessment tools like the Ishikawa diagram and Failure Mode and Effect Analysis supports this. Statistical methods, particularly Design of Experiments, have been crucial for identifying and optimizing key variables. This leads to the development of a Method Operable Design Region (MODR). The MODR sets the limits for the analytical method's reliable results, which means that changes can be made after approval without having to go through the whole process again. Box-Behnken and Central Composite are two common designs that are used to determine how various factors interact in order to ensure that methods perform effectively. Quality-by-Design-based control strategies combine lifecycle management and real-time monitoring to make sure that quality continues to improve more effectively. Literature screening and data organization were performed using Microsoft Excel (Microsoft Corporation, Redmond, WA, USA). Reference management and duplicate removal were carried out using EndNote (Clarivate Analytics). Database searches were conducted across PubMed, Web of Science, Elsevier, and Google Scholar using predefined keywords.
Chauhan et al. (Fri,) studied this question.