Quality by design (QbD) is an essential concept for modern manufacturing processes of pharmaceutical products. Understanding the science behind manufacturing processes is crucial; however, the complexity of the manufacturing processes makes implementing QbD challenging. In this study, structural equation modeling (SEM) was applied to understand the causal relationships between variables such as process parameters, material attributes, and quality attributes. Based on SEM analysis, we identified a model composed of the above-mentioned variables and their latent factors without including observational data. Difficulties in fitting the observed data to the proposed model are often encountered in SEM analysis. To address this issue, we adopted Bayesian estimation with Markov chain Monte Carlo simulation. The tableting process involving the wet-granulation process for acetaminophen was employed as a model case for the manufacturing process. The results indicate that SEM analysis could be useful for implementing QbD for the manufacturing processes of pharmaceutical products.
Keywords: Bayesian estimation; Markov chain Monte Carlo simulation; quality by design; structural equation modeling; wet-granulation tableting.