过程分析技术
拉曼光谱
过程(计算)
工艺工程
软件
偏最小二乘回归
机组运行
医药制造业
工业与生产工程
计算机科学
化学工程
在制品
工程类
机械工程
操作系统
运营管理
物理
机器学习
光学
生物
生物信息学
程序设计语言
作者
Yuma Miyai,Anna V. Forzano,Cameron Armstrong,Brian J. Marquardt,L. Rogers,Thomas D. Roper
标识
DOI:10.1021/acs.oprd.1c00299
摘要
The strategies and experimental methods for implementation of process analytical technology (PAT) on the mobile pharmaceutical manufacturing system, Pharmacy on Demand (PoD), are discussed. With multiple processes to be monitored on the PoD end-to-end continuous manufacturing process, PAT and its real-time process monitoring capability play a significant role in ensuring final product quality. Here, we discuss PAT implementation for real-time monitoring of an intermediate and API concentrations with in-line Fourier-transformed infrared and Raman spectroscopy for the five-step continuous synthesis of ciprofloxacin on the PoD synthesis unit. Two partial least squares regression models were built and verified with flow chemistry experiments to obtain a root-mean-square error of prediction (RMSEP) of 2.2 mg/mL with a relative error of 2.8% for the step 2 FlowIR model and a RMSEP of 0.9 mg/mL with a relative error of 2.8% for the step 5 Raman model. These models were deployed during an 11 h step 1–3 and a 5 h step 4–5 continuous ciprofloxacin synthesis run performed on the PoD system. In these runs, the real-time prediction of intermediate and product concentration was achieved with an online model processing software (Solo_Predictor) and a PAT data collection and management software (synTQ).
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