Literature DB >> 24522402

Population pharmacokinetics of afatinib, an irreversible ErbB family blocker, in patients with various solid tumors.

Matthias Freiwald1, Ulrike Schmid, Angele Fleury, Sven Wind, Peter Stopfer, Alexander Staab.   

Abstract

PURPOSE: This population pharmacokinetic model was developed to characterize the pharmacokinetics of the oral irreversible ErbB family blocker afatinib in patients with solid tumors and to investigate the impact of selected intrinsic and extrinsic factors.
METHODS: Data from 927 patients (4,460 plasma concentrations) with advanced solid tumors in 7 Phase II or III studies were analyzed. Afatinib was administered orally in continuous 3 or 4 week cycles (starting dose 20, 40 or 50 mg once-daily). Plasma concentration-time data for up to 7 months dosing were analyzed using nonlinear mixed-effects modeling.
RESULTS: The pharmacokinetic profile of afatinib was best described by a two-compartment disposition model with first-order absorption and linear elimination. There was a slightly more than proportional increase in exposure with increasing dose, accounted for by a dose-dependent relative bioavailability. For the therapeutic dose of 40 mg, the estimated apparent total clearance and distribution volume at steady state were 734 mL/min and 2,370 L, respectively. While food intake, body weight, gender, Eastern Cooperative Oncology Group performance score, renal function, and the level of alkaline phosphatase, lactate dehydrogenase or total protein were statistically significant covariates influencing afatinib exposure, none resulted in a proportional change in exposure of more than 27.8 % in a typical patient at model extremes (2.5th and 97.5th percentiles of baseline values for continuous covariates). In simulations of the individual covariate effects, none caused a change in the typical profile exceeding the observed variability range (90 % prediction interval) of afatinib.
CONCLUSION: This population pharmacokinetic model adequately described the pharmacokinetics of afatinib in different cancer patient populations and therefore can be used for simulations exploring covariate effects and possible dose adaptations. The effect size for each of the individual covariates is not considered clinically relevant.

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Year:  2014        PMID: 24522402     DOI: 10.1007/s00280-014-2403-2

Source DB:  PubMed          Journal:  Cancer Chemother Pharmacol        ISSN: 0344-5704            Impact factor:   3.333


  16 in total

1.  Conflicting meal recommendations for oral oncology drugs: pose risks to patient care?

Authors:  Guo Yu; Dan-Na Wu; Yan Gong; Guo-Fu Li; Hong-Hao Zhou
Journal:  Eur J Clin Pharmacol       Date:  2018-03-13       Impact factor: 2.953

2.  [Pharmacotherapy of solid tumors. New hopes and frustrations].

Authors:  V Grünwald; M Rickmann
Journal:  Internist (Berl)       Date:  2014-10       Impact factor: 0.743

3.  Pharmacokinetics of afatinib in subjects with mild or moderate hepatic impairment.

Authors:  David Schnell; Susanne Buschke; Holger Fuchs; Dietmar Gansser; Rainer-Georg Goeldner; Martina Uttenreuther-Fischer; Peter Stopfer; Sven Wind; Marc Petersen-Sylla; Atef Halabi; Rüdiger Koenen
Journal:  Cancer Chemother Pharmacol       Date:  2014-06-07       Impact factor: 3.333

4.  Influence of Renal Impairment on the Pharmacokinetics of Afatinib: An Open-Label, Single-Dose Study.

Authors:  Sabrina Wiebe; David Schnell; Raimund Külzer; Dietmar Gansser; Anne Weber; Gudrun Wallenstein; Atef Halabi; Anja Conrad; Sven Wind
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2017-06       Impact factor: 2.441

Review 5.  Clinical Pharmacokinetics and Pharmacodynamics of Afatinib.

Authors:  Sven Wind; David Schnell; Thomas Ebner; Matthias Freiwald; Peter Stopfer
Journal:  Clin Pharmacokinet       Date:  2017-03       Impact factor: 6.447

6.  Risk Factors for Severe Diarrhea with an Afatinib Treatment of Non-Small Cell Lung Cancer: A Pooled Analysis of Clinical Trials.

Authors:  Ashley M Hopkins; Anh-Minh Nguyen; Christos S Karapetis; Andrew Rowland; Michael J Sorich
Journal:  Cancers (Basel)       Date:  2018-10-15       Impact factor: 6.639

7.  The impact of age and performance status on the efficacy of osimertinib in patients with EGFR T790M-positive non-small cell lung cancer.

Authors:  Hyun-Il Gil; Sang-Won Um
Journal:  J Thorac Dis       Date:  2020-03       Impact factor: 2.895

Review 8.  Toward Optimum Benefit-Risk and Reduced Access Lag For Cancer Drugs in Asia: A Global Development Framework Guided by Clinical Pharmacology Principles.

Authors:  K Venkatakrishnan; C Burgess; N Gupta; A Suri; T Takubo; X Zhou; D DeMuria; M Lehnert; K Takeyama; S Singhvi; A Milton
Journal:  Clin Transl Sci       Date:  2016-02-05       Impact factor: 4.689

9.  Modeling Exposure-Driven Adverse Event Time Courses in Oncology Exemplified by Afatinib.

Authors:  Ronald Niebecker; Hugo Maas; Alexander Staab; Matthias Freiwald; Mats O Karlsson
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-02-27

10.  Population pharmacokinetics of afatinib and exposure-safety relationships in Japanese patients with EGFR mutation-positive non-small cell lung cancer.

Authors:  Keiko Nakao; Shinji Kobuchi; Shuhei Marutani; Ayano Iwazaki; Akihiro Tamiya; Shunichi Isa; Kyoichi Okishio; Masaki Kanazu; Motohiro Tamiya; Tomonori Hirashima; Kimie Imai; Toshiyuki Sakaeda; Shinji Atagi
Journal:  Sci Rep       Date:  2019-12-03       Impact factor: 4.379

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