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.

质量源于设计 (QbD) 是现代医药产品制造过程的基本概念。了解制造过程背后的科学至关重要；然而，制造过程的复杂性使得实施 QbD 具有挑战性。在本研究中，应用结构方程模型 (SEM) 来了解过程参数、材料属性和质量属性等变量之间的因果关系。基于SEM分析，我们确定了一个由上述变量及其潜在因素组成的模型，不包括观测数据。在 SEM 分析中经常遇到将观察到的数据拟合到所提出的模型中的困难。为了解决这个问题，我们采用了贝叶斯估计和马尔可夫链蒙特卡罗模拟。涉及对乙酰氨基酚湿法制粒工艺的压片工艺被用作制造工艺的典型案例。结果表明，SEM 分析可用于在药品制造过程中实施 QbD。