Feng Jin1, Yuying Gao2, Huafeng Zhou3, Lorna Fang4, Xiaoming Li5, Srini Ramanathan6. 1. Gilead Sciences, Inc., 333 Lakeside Drive, Foster City, CA, USA. feng.jin@gilead.com. 2. Quantitative Solutions, LP., Menlo Park, CA, USA. 3. CTI Biopharma, Seattle, WA, USA. 4. Onyx Pharmaceuticals, South San Francisco, CA, USA. 5. Gilead Sciences, Inc., Seattle, WA, USA. 6. Gilead Sciences, Inc., 333 Lakeside Drive, Foster City, CA, USA.
Abstract
PURPOSE: Idelalisib is a potent PI3Kδ inhibitor that was recently approved for treating hematologic malignancies. The objective of this analysis was to develop a population pharmacokinetic model for idelalisib and its inactive metabolite GS-563117 and to evaluate the impact of covariates on idelalisib/GS-563117 PK. METHODS: Data from 10 phase I or II studies in healthy volunteers or patients with hematologic malignancies (n = 736) were analyzed using NONMEM. Stepwise forward addition followed by backward elimination was implemented in the covariate (age, gender, race, body weight, baseline CLcr, AST, ALT, disease status, and type of cancer) model building process. Various model assessment methods were used to evaluate the models. RESULTS: Idelalisib plasma PK was best described by a two-compartment model with first-order absorption, first-order elimination from the central compartment, and a lag time. A nonlinear relationship between dose and relative bioavailability was included in the final model. Two statistically significant covariates were identified and incorporated into the final model: health status (healthy vs. patient) on CL/F and Q/F and body weight on CL/F. Despite being a statistically significant covariate, the effect of body weight on idelalisib exposures was weak, as evidenced by minor changes of steady-state exposure (C trough: 16%; AUC and C max: 10%) for a patient with extreme body weight (5th and 95th percentile) relative to the typical patient, and not considered to be clinically relevant. CONCLUSIONS: PopPK models were developed to adequately describe the plasma concentrations of idelalisib and GS-563117. There were no covariate that had a clinically meaningful impact on idelalisib or GS-563117 exposure.
PURPOSE:Idelalisib is a potent PI3Kδ inhibitor that was recently approved for treating hematologic malignancies. The objective of this analysis was to develop a population pharmacokinetic model for idelalisib and its inactive metabolite GS-563117 and to evaluate the impact of covariates on idelalisib/GS-563117 PK. METHODS: Data from 10 phase I or II studies in healthy volunteers or patients with hematologic malignancies (n = 736) were analyzed using NONMEM. Stepwise forward addition followed by backward elimination was implemented in the covariate (age, gender, race, body weight, baseline CLcr, AST, ALT, disease status, and type of cancer) model building process. Various model assessment methods were used to evaluate the models. RESULTS:Idelalisib plasma PK was best described by a two-compartment model with first-order absorption, first-order elimination from the central compartment, and a lag time. A nonlinear relationship between dose and relative bioavailability was included in the final model. Two statistically significant covariates were identified and incorporated into the final model: health status (healthy vs. patient) on CL/F and Q/F and body weight on CL/F. Despite being a statistically significant covariate, the effect of body weight on idelalisib exposures was weak, as evidenced by minor changes of steady-state exposure (C trough: 16%; AUC and C max: 10%) for a patient with extreme body weight (5th and 95th percentile) relative to the typical patient, and not considered to be clinically relevant. CONCLUSIONS: PopPK models were developed to adequately describe the plasma concentrations of idelalisib and GS-563117. There were no covariate that had a clinically meaningful impact on idelalisib or GS-563117 exposure.
Entities:
Keywords:
Covariates; Idelalisib; PI3Kδ; Population pharmacokinetics
Authors: Anna Mueller-Schoell; Stefanie L Groenland; Oliver Scherf-Clavel; Madelé van Dyk; Wilhelm Huisinga; Robin Michelet; Ulrich Jaehde; Neeltje Steeghs; Alwin D R Huitema; Charlotte Kloft Journal: Eur J Clin Pharmacol Date: 2020-11-09 Impact factor: 2.953
Authors: Maria Bhatti; Thomas Ippolito; Cory Mavis; Juan Gu; Mitchell S Cairo; Megan S Lim; Francisco Hernandez-Ilizaliturri; Matthew J Barth Journal: Oncotarget Date: 2018-04-24