Comparison of chemometrics strategies for the spectroscopic monitoring of active pharmaceutical ingredients in chemical reactions
نویسندگان
چکیده
The Process Analytical Technology (PAT) initiative promoted by the Food and Drug Administration (FDA) encourages pharmaceutical companies to increase use of new analytical technologies perform constant monitoring critical quality attributes (CQA), allowing a better understanding control process. This paper presents practical framework based on different dimension-reduction methods as well calibration aimed at following over time chemical experiments organized in batches. To illustrate it, this uses data collected research development context towards industrial production. methodological aims reach two objectives. first objective is visualize interpret real time, or off-line, kinetics reactions using methods: principal component analysis (PCA), non-negative matrix factorization (NMF) multivariate curve resolution (MCR). results show that, due their additional constraints, NMF MCR allow interpretability than PCA with comparable fit. Moreover, eventough come from fields, algorithms share many similarities produce close results. second predict concentrations time. For objective, partial least squares regression (PLSR) used one-step approach compared two-step combining PCA, MCR. that spectra scores obtained unsupervised approaches can be main compounds continuously all reaction good precision gain interpretability. both objectives, possible model validation indices are also discussed including leave-one-batch-out approach.
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ژورنال
عنوان ژورنال: Chemometrics and Intelligent Laboratory Systems
سال: 2021
ISSN: ['1873-3239', '0169-7439']
DOI: https://doi.org/10.1016/j.chemolab.2021.104273