Department of Pharmaceutical Technology and Biopharmacy, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania.
Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary.
Molecules. 2022 Jul 28;27(15):4846. doi: 10.3390/molecules27154846.
The release of the FDA's guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.
FDA 发布的关于过程分析技术的指南激励并支持制药行业通过更深入地了解产品性能和工艺相互作用来提供一致质量的药物。自 2004 年以来，由于先进的分析传感器和化学计量学工具的发展，实现这种高水平控制的技术机会已经有了相当大的发展。然而，它们向高度监管的制药领域的转移是有限的。在这方面，数据融合策略已广泛应用于食品或化学等不同领域，以提供更稳健的分析平台性能。本调查通过从其他领域确定转移机会，评估了在 PAT 概念中实施数据融合的挑战和机遇。特别关注制药生产中可用的数据类型及其与数据融合策略的兼容性。此外，还讨论了与 Pharma 4.0 的集成。
