Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010 Graz, Austria; Institute of Automation and Control, Graz University of Technology, Inffeldgasse 21b, 8010 Graz, Austria.
Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010 Graz, Austria.
Int J Pharm. 2023 Jun 25;641:123038. doi: 10.1016/j.ijpharm.2023.123038. Epub 2023 May 12.
ConsiGma-25 is a continuous production plant integrating a twin-screw granulation, fluid bed drying, granule conditioning, and a tableting unit. The particle size distribution (PSD), active pharmaceutical ingredient (API) content, and liquid content of wet granules after twin-screw granulation affect the quality of intermediate and final products. This paper proposes methods for real-time monitoring of these quantities and control-oriented modeling of the granulator. The PSD of wet granules is monitored via an in-line process analytical technology (PAT) probe based on the spatial velocimetry principle. The algorithm for signal processing and evaluation of PSD characteristics is developed and applied to the acquired PSD data. A dynamic process model predicting PSD characteristics from granulation parameters is trained via the local linear model tree (LoLiMoT) approach. The experimental data required for the model training are collected via systematically designed excitation runs. Finally, the performance of the identified model is examined and verified by means of a new set of validation runs. Furthermore, an in-line PAT probe based on Raman spectroscopy is developed and integrated after the granulator. The API- and liquid content of produced wet granules are evaluated from the spectral data by means of chemometric modeling, and chemometric models are validated on a separate set of experimental data. The solutions proposed in this research can be used as a reliable (and necessary) basis for the development of advanced quality-by-design control concepts (e.g., PSD process control). Such concepts would ultimately improve the ConsiGma-25 process performance in terms of robustness against disturbances and quality of intermediate and final products.
ConsiGma-25 是一个连续生产设备，集成了双螺杆造粒、流化床干燥、颗粒调节和压片单元。双螺杆造粒后的颗粒大小分布（PSD）、活性药物成分（API）含量和湿颗粒的液体含量会影响中间产品和最终产品的质量。本文提出了实时监测这些量的方法和面向控制的造粒机建模。湿颗粒的 PSD 通过基于空间速度测量原理的在线过程分析技术（PAT）探头进行监测。开发了用于信号处理和 PSD 特征评估的算法，并将其应用于获得的 PSD 数据。通过局部线性模型树（LoLiMoT）方法训练了一个从造粒参数预测 PSD 特征的动态过程模型。模型训练所需的实验数据通过系统设计的激励运行收集。最后，通过一组新的验证运行来检查和验证所识别模型的性能。此外，在造粒机后开发并集成了一种基于拉曼光谱的在线 PAT 探头。通过化学计量学建模从光谱数据中评估生产湿颗粒中的 API 和液体含量，并在另一组实验数据上验证化学计量学模型。本研究中提出的解决方案可以作为开发先进的质量源于设计控制概念（例如 PSD 过程控制）的可靠（和必要）基础。这些概念最终将提高 ConsiGma-25 工艺在抗干扰性和中间产品和最终产品质量方面的性能。
