In-silico Prediction of CYP450 Inhibition-mediated Drug-drug Interactions by Multiple Linear Regression Analysis
| Autor: | Yu-Hsiang Peng, 彭煜翔 |
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| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 Drug-drug interactions (DDIs) have always been significant issues in the drug development or clinical use, especially by way of cytochrome P450 (CYP450) 3A4, 2D6 and 2C9 inhibitions as the most common ones. The risk and cost of the new drug development may be reduced if the drug properties and the potential DDIs can be understood in advance before the new drug is released, or even in the early stage of the drug development. Therefore, in-silico studies would be of significant importance. The U.S. Food and Drug Administration (FDA) has issued the draft guidance for drug interaction studies since 1997, and the guidance has been updated, in which quantitative prediction models have been proposed. Previous studies have suggested that the drug properties such as physicochemical properties and pharmacokinetic parameters are associated with the metabolism-based DDIs. Additionally, a study investigates CYP induction-mediated DDIs and identifies the significant factors using multiple linear regression models. However, no studies comprehensively evaluate the impact of all these drug properties on CYP inhibition-mediated DDIs. Thus, we conducted a retrospective data analysis, establishing prediction models by multiple linear regression analysis to identify the significant factors that affect the CYP3A4, 2D6 and 2C9 inhibition-mediated DDIs, and evaluate the model goodness of fit, prediction error and predictability. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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