The Application of SVR Model in the Improvement of QbD: A case study of the extraction of podophyllotoxin.

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The Application of SVR Model in the Improvement of QbD: A case study of the extraction of podophyllotoxin.

Drug Dev Ind Pharm. 2018 Apr 20;:1-24

Authors: Zhai CH, Xuan JB, Fan HL, Zhao TF, Jiang JL

Abstract
In order to make a further optimization of process design via increasing the stability of design space, we brought in the model of Support Vector Regression (SVR). In this work, the extraction of podophyllotoxin was researched as a case study based on QbD. We compared the fitting effect of SVR and the most used quadratic polynomial model (QPM) in QbD, and an analysis was made between the two design spaces obtained by SVR and QPM. As a result, the SVR stayed ahead of QPM in prediction accuracy, the stability of model and the generalization ability. The introduction of SVR into QbD made the extraction process of podophyllotoxin well designed and easier to control. The better fitting effect of SVR improved the application effect of QbD and the universal applicability of SVR, especially for nonlinear, complicated and weak-regularity problems, widened the application field of QbD.

PMID: 29676171 [PubMed - as supplied by publisher]

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