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A physiologically based pharmacokinetic - pharmacodynamic modelling approach to predict incidence of neutropenia as a result of drug-drug interactions of paclitaxel in cancer patients.
- Source :
-
European Journal of Pharmaceutical Sciences . Jul2020, Vol. 150, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
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Abstract
- Paclitaxel is the backbone of standard chemotherapeutic regimens used in a number of malignancies and is frequently given with concomitant medications. Newly developed oncolytic agents, including tyrosine kinase inhibitors are often shown to be CYP3A4 and P-gp inhibitors. The aim of this study was to develop a PBPK model for intravenously administered paclitaxel in order to predict the incidence of neutropenia and to estimate the DDI potential as a victim drug. The dose-dependent effects on paclitaxel plasma protein binding, volume of distribution and drug clearance were considered for dose levels of 80 mg/m2, 135 mg/m2 and 175 mg/m2. A pharmacodynamics model that incorporate the impact of paclitaxel on the neutrophil was developed. The relative metabolic clearance via CYP3A4 and CYP2C8, the renal clearance as well as P-gp mediated biliary clearance were incorporated in the model in order to assess the neutropenia in the presence of DDI. The developed PBPK-PD model was able to recover the drop in neutrophils observed after the administration of 175mg/m2 of paclitaxel over a 3-h duration. The mean nadir observed was 1.9 × 109 neutrophils/L and was attained after 10 days of treatment, and a fraction of 47% of the population was predicted to have at some point a neutropenia including 12% with severe neutropenia. In the case of concomitant administration of ketoconazole, 39% of the population was predicted to suffer from severe neutropenia. In summary, PBPK-PD modeling allows a priori prediction of DDIs and safety events involving complex combination therapies which are often utilized in an oncology setting. Image, graphical abstract [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09280987
- Volume :
- 150
- Database :
- Academic Search Index
- Journal :
- European Journal of Pharmaceutical Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 143740269
- Full Text :
- https://doi.org/10.1016/j.ejps.2020.105355