Improving tablet coating robustness by selecting critical process parameters from retrospective data

Abstract Context: Although tablet coating processes are widely used in the pharmaceutical industry, they often lack adequate robustness. Up-scaling can be challenging as minor changes in parameters can lead to varying quality results. Objective: To select critical process parameters (CPP) using retrospective data of a commercial product and to establish a design of experiments (DoE) that would improve the robustness of the coating process. Materials and methods: A retrospective analysis of data from 36 commercial batches. Batches were selected based on the quality results generated during batch release, some of which revealed quality deviations concerning the appearance of the coated tablets. The product is already marketed and belongs to the portfolio of a multinational pharmaceutical company. Results: The Statgraphics 5.1 software was used for data processing to determine critical process parameters in order to propose new working ranges. Discussion and conclusions: This study confirms that it is possible to determine the critical process parameters and create design spaces based on retrospective data of commercial batches. This type of analysis is thus converted into a tool to optimize the robustness of existing processes. Our results show that a design space can be established with minimum investment in experiments, since current commercial batch data are processed statistically.