Univ. Bordeaux, CNRS, Arts et Metiers Institute of Technology, Bordeaux INP, INRAE, I2M Bordeaux, F-33400 Talence, France.
Research and Development Division, F. Hoffmann-La Roche AG, Basel, Switzerland.
Int J Pharm. 2022 Jul 25;623:121949. doi: 10.1016/j.ijpharm.2022.121949. Epub 2022 Jun 23.
Predicting tablet defects, such as capping, that might occur during manufacturing, is a challenge in the pharmaceutical industry. In the literature, different parameters were presented to predict capping but no general consensus seems to have been reached yet. In this article, we chose to study a wide range of products (18 formulations, 8 of which presenting capping) to predict capping on biconvex tablets using the properties characterized on defect-free flat-faced tablets (tensile strength, solid fraction, elastic recovery, etc.), made using the same process parameters. Single parameters and predictive indices presented in the literature were evaluated on this set of formulations and were found not suitable to predict capping. A predictive model was then developed using a decision tree analysis and was found to depend only on three in-die tablet properties: the plastic energy per volume, the in-die elastic recovery and the residual die-wall pressure. This model was tested on another set of 13 formulations chosen to challenge it. The capping behavior of 29 out of the 31 formulations studied in total was well estimated using the developed model with only two products which were predicted to cap and did not. This shows the potential of the used approach in terms of risk analysis and assessment for capping occurrence.
预测片剂缺陷(如麻点)在生产过程中可能发生,是制药行业的一个挑战。在文献中,已经提出了不同的参数来预测麻点,但似乎尚未达成普遍共识。在本文中,我们选择研究广泛的产品(18 种配方,其中 8 种存在麻点),使用相同的工艺参数,通过对无缺陷的平面片剂(拉伸强度、固体分数、弹性恢复等)进行特性分析,来预测双凸片剂上的麻点。文献中提出的单一参数和预测指标在这组配方上进行了评估,发现不适合预测麻点。然后使用决策树分析开发了一个预测模型,发现该模型仅取决于三个压模内片剂特性:单位体积塑性能量、压模内弹性恢复和残留模壁压力。该模型在另一组 13 种配方上进行了测试,以验证其适用性。该模型能够很好地预测总共研究的 31 种配方中的 29 种的麻点行为,只有两种预测为麻点的产品未出现麻点。这表明了所使用的方法在分析和评估麻点发生风险方面的潜力。