Gyürkés Martin, Madarász Lajos, Köte Ákos, Domokos András, Mészáros Dániel, Beke Áron Kristóf, Nagy Brigitta, Marosi György, Pataki Hajnalka, Nagy Zsombor Kristóf, Farkas Attila
Department of Organic Chemistry and Technology, Budapest University of Technology and Economics (BME), Műegyetem rakpart 3, H-1111 Budapest, Hungary.
Pharmaceutics. 2020 Nov 20;12(11):1119. doi: 10.3390/pharmaceutics12111119.
The present paper reports a thorough continuous powder blending process design of acetylsalicylic acid (ASA) and microcrystalline cellulose (MCC) based on the Process Analytical Technology (PAT) guideline. A NIR-based method was applied using multivariate data analysis to achieve in-line process monitoring. The process dynamics were described with residence time distribution (RTD) models to achieve deep process understanding. The RTD was determined using the active pharmaceutical ingredient (API) as a tracer with multiple designs of experiment (DoE) studies to determine the effect of critical process parameters (CPPs) on the process dynamics. To achieve quality control through material diversion from feeding data, soft sensor-based process control tools were designed using the RTD model. The operation block model of the system was designed to select feasible experimental setups using the RTD model, and feeder characterizations as digital twins, therefore visualizing the output of theoretical setups. The concept significantly reduces the material and instrumental costs of process design and implementation.
本文报道了基于过程分析技术（PAT）指南的乙酰水杨酸（ASA）和微晶纤维素（MCC）的全面连续粉末混合工艺设计。采用基于近红外的方法并结合多变量数据分析来实现在线过程监测。用停留时间分布（RTD）模型描述过程动力学以深入理解过程。使用活性药物成分（API）作为示踪剂，通过多个实验设计（DoE）研究来确定RTD，以确定关键过程参数（CPPs）对过程动力学的影响。为了通过从进料数据进行物料转移来实现质量控制，使用RTD模型设计了基于软传感器的过程控制工具。系统的操作模块模型旨在使用RTD模型选择可行的实验设置，并将进料器特性作为数字孪生体，从而可视化理论设置的输出。该概念显著降低了过程设计和实施的材料及仪器成本。
