Population pharmacokinetic-pharmacodynamic modeling of serum biomarkers as predictors of tumor dynamics following lenvatinib treatment in patients with radioiodine-refractory differentiated thyroid cancer (RR-DTC).


Journal

CPT: pharmacometrics & systems pharmacology
ISSN: 2163-8306
Titre abrégé: CPT Pharmacometrics Syst Pharmacol
Pays: United States
ID NLM: 101580011

Informations de publication

Date de publication:
26 Mar 2024
Historique:
revised: 27 02 2024
received: 28 11 2023
accepted: 08 03 2024
medline: 26 3 2024
pubmed: 26 3 2024
entrez: 26 3 2024
Statut: aheadofprint

Résumé

Lenvatinib is a receptor tyrosine kinase (RTK) inhibitor targeting vascular endothelial growth factor (VEGF) receptors 1-3, fibroblast growth factor (FGF) receptors 1-4, platelet-derived growth factor receptor-α (PDGFRα), KIT, and RET that have been implicated in pathogenic angiogenesis, tumor growth, and cancer. The primary objective of this work was to evaluate, by establishing quantitative relationships, whether lenvatinib exposure and longitudinal serum biomarker data (VEGF, Ang-2, Tie-2, and FGF-23) are predictors for change in longitudinal tumor size which was assessed based on data from 558 patients with radioiodine-refractory differentiated thyroid cancer (RR-DTC) receiving either lenvatinib or placebo treatment. Lenvatinib PK was best described by a 3-compartment model with simultaneous first- and zero-order absorption and linear elimination from the central compartment with significant covariates (body weight, albumin <30 g/dL, ALP>ULN, RR-DTC, RCC, HCC subjects, and concomitant CYP3A inhibitors). Except for body weight, none of the covariates have any clinically meaningful effect on exposure to lenvatinib. Longitudinal biomarker measurements over time were reasonably well defined by a PK/PD model with common EC

Identifiants

pubmed: 38528813
doi: 10.1002/psp4.13130
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Eisai Ltd.
Organisme : Eisai Co.
Organisme : Eisai Inc

Informations de copyright

© 2024 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.

Références

Khan K, Wu F, Cruz‐Munoz W, Kerbel R. Ang‐2 inhibitors and tie‐2 activators: potential therapeutics in perioperative treatment of early stage cancer. EMBO Mol Med. 2021;13(7):e08253.
Koizumi Y, Hirooka M, Hiraoka A, et al. Lenvatinib‐induced thyroid abnormalities in unresectable hepatocellular carcinoma. Endocr J. 2019;66(9):787‐792.
LENVIMA. [package insert]. Hatfield, Hertfordshire. UK: Eisai Ltd.
Atkinson AJ, Colburn WA, DeGruttola VG, et al. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69:89‐95. doi:10.1067/mcp.2001.113989
Finn RS, Kudo M, Cheng A‐L, et al. Pharmacodynamic biomarkers predictive of survival benefit with Lenvatinib in unresectable hepatocellular carcinoma: from the phase III REFLECT study. Clin Cancer Res. 2021;27(17):4848‐4858. doi:10.1158/1078-0432.CCR-20-4219
Hayato S, Shumaker S, Ferry J, Binder T, Dutcus CE, Hussein Z. Exposure–response analysis and simulation of lenvatinib safety and efficacy in patients with radioiodine‐refractory differentiated thyroid cancer. Cancer Chemother Pharmacol. 2018;82:971‐978. doi:10.1007/s00280-018-3687-4
Claret L, Girard P, Hoff PM, et al. Model‐based prediction of phase III overall survival in colorectal cancer on the basis of phase II tumor dynamics. J Clin Oncol. 2009;27:4103‐4108. doi:10.1200/JCO.2008.21.0807
Claret L, Lu JF, Sun YN, Bruno R. Development of a modeling framework to simulate efficacy endpoints for motesanib in patients with thyroid cancer. Cancer Chemother Pharmacol. 2010;66:1141‐1149. doi:10.1007/s00280-010-1449-z
Wang Y, Sung C, Dartois C, et al. Elucidation of relationship between tumor size and survival in non‐small‐cell lung cancer patients can aid early decision making in clinical drug development. Clin PharmacolTher. 2009;86:167‐174. doi:10.1038/clpt.2009.64
Lu JF, Claret L, Sutjandra L, et al. Population pharmacokinetic/pharmacodynamic modeling for the time course of tumor shrinkage by motesanib in thyroid cancer subjects. Cancer Chemother Pharmacol. 2010;66:1151‐1158. doi:10.1007/s00280-010-1456-0
Bruno R, Lu YF, Sun YN, Claret L. A modeling and simulation framework to support early clinical drug development decisions in oncology. J Clin Pharmacol. 2011;51:6‐8. doi:10.1177/0091270010376970
Schlumberger M, Tahara M, Wirth LJ, et al. Lenvatinib versus placebo in radioiodine‐refractory thyroid cancer. N Engl J Med. 2015;372(7):621‐630. doi:10.1056/NEJMoa1406470
Brose MS, Panaseykin Y, Konda B. A randomized study of lenvatinib 18 mg vs 24 mg in patients with radioiodine‐refractory differentiated thyroid cancer. J Clin Endocrinol Metab. 2022;107(3):776‐787. doi:10.1210/clinem/dgab731
Bauer RJ. NONMEM tutorial part II: estimation methods and advanced examples. CPT Pharmacometrics Syst Pharmacol. 2019;8(8):538‐556. doi:10.1002/psp4.12422
Gupta A, Jarzab B, Capdevila J, Shumaker R, Hussein Z. Population pharmacokinetic analysis of lenvatinib in healthy subjects and patients with cancer. Br J Clin Pharmacol. 2016;81(6):1124‐1133. doi:10.1111/bcp.12907
Motzer R, Alekseev B, Rha SY, et al. Lenvatinib plus pembrolizumab or Everolimus for advanced renal cell carcinoma. N Engl J Med. 2021;384:1289‐1300. doi:10.1056/NEJMoa2035716
Hansson EK, Amantea MA, Westwood P, et al. PKPD modeling of VEGF, sVEGFR‐2, sVEGFR‐3, and sKIT as predictors of tumor dynamics and overall survival following sunitinib treatment in GIST. CPT Pharmacometrics Syst Pharmacol. 2013;2(11):e84. doi:10.1038/psp.2013.61
Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction‐corrected visual predictive checks for diagnosing nonlinear mixed‐effects models. AAPS J. 2011;13:143‐151. doi:10.1208/s12248-011-9255-z
Yafune A, Ishiguro M. Bootstrap approach for constructing confidence intervals for population pharmacokinetic parameters. Ι: a use of bootstrap standard error. Stat Med. 1999;18(5):581‐599. doi:10.1002/(sici)1097-0258(19990315)18:5<581::aid-sim47>3.0.co;2-1
Hussein Z, Mizuo H, Hayato S, Namiki M, Shumaker R. Clinical pharmacokinetic and pharmacodynamic profile of Lenvatinib, an orally active, small‐molecule, multitargeted tyrosine kinase inhibitor. Eur J Drug Metab Pharmacokinet. 2017;42(6):903‐914. doi:10.1007/s13318-017-0403-4
Tamai T, Hayato S, Hojo S, et al. Dose finding of Lenvatinib in subjects with advanced hepatocellular carcinoma based on population pharmacokinetic and exposure‐response analyses. J Clin Pharmacol. 2017;57(9):1138‐1147. doi:10.1002/jcph.917
Matsubara N, Naito Y, Nakano K, et al. Lenvatinib in combination with everolimus in patients with advanced or metastatic renal cell carcinoma: a phase 1 study. Int J Urol. 2018;25(11):922‐928. doi:10.1111/iju.13776
Cabanillas ME, Schlumberger M, Jarzab B, et al. A phase 2 trial of lenvatinib (E7080) in advanced, progressive, radioiodine‐refractory, differentiated thyroid cancer: a clinical outcomes and biomarker assessment. Cancer. 2015;121(16):2749‐2756. doi:10.1002/cncr.29395
Schlumberger M, Jarzab B, Cabanillas ME, et al. A phase II trial of the multitargeted tyrosine kinase inhibitor Lenvatinib (E7080) in advanced medullary thyroid cancer. Clin Cancer Res. 2016;22(1):44‐53. doi:10.1158/1078-0432.CCR-15-1127
Zhu A, Llovet J, Kobayashi M, et al. Exploratory circulating biomarker analyses: lenvatinib + pembrolizumab (L + P) in a phase 1b trial in unresectable hepatocellular carcinoma (uHCC). J Clin Oncol. 2021;39(15_suppl):4084. doi:10.1200/JCO.2021.39.15_suppl.4084
Tahara M, Schlumberger M, Elisei R, et al. Exploratory analysis of biomarkers associated with clinical outcomes from the study of lenvatinib in differentiated cancer of the thyroid. Eur J Cancer. 2017;75:213‐221. doi:10.1016/j.ejca.2017.01.013

Auteurs

Seiichi Hayato (S)

Eisai Co., Ltd., Tokyo, Japan.

Sree Harsha Sreerama Reddy (SH)

Eisai Inc., Nutley, New Jersey, USA.

Bojan Lalovic (B)

Eisai Inc., Nutley, New Jersey, USA.

Taro Hihara (T)

Eisai Co., Ltd., Tokyo, Japan.

Taisuke Hoshi (T)

Eisai Co., Ltd., Tokyo, Japan.

Yasuhiro Funahashi (Y)

Eisai Co., Ltd., Tokyo, Japan.

Jagadeesh Aluri (J)

Eisai Inc., Nutley, New Jersey, USA.

Osamu Takenaka (O)

Eisai Co., Ltd., Tokyo, Japan.

Sanae Yasuda (S)

Eisai Co., Ltd., Tokyo, Japan.

Ziad Hussein (Z)

Eisai Ltd., Hatfield, UK.

Classifications MeSH