A physiologically based pharmacokinetic - pharmacodynamic modelling approach to predict incidence of neutropenia as a result of drug-drug interactions of paclitaxel in cancer patients

• DOI: 10.1016/j.ejps.2020.105355
• Publication Date: 2020-05-18T17:54:16Z
• Authors: Mailys De Sousa M...; Oliver Hatley; Katherine Linda Gill; Karen Rowland Yeo; Alice Ban Ke
• Keywords: Adult; Male; Sulfonamides; Indazoles; Neutropenia; Paclitaxel; Middle Aged; Antineoplastic Agents, Phytogenic; Models, Biological; 3. Good health; Cytochrome P-450 CYP2C8; 03 medical and health sciences; Drug Delivery Systems; Ketoconazole; Pyrimidines; 0302 clinical medicine; Verapamil; Neoplasms; Cytochrome P-450 CYP3A; Humans; Drug Interactions; Female; Aged

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.