CPT: Pharmacometrics & Systems Pharmacology (Jul 2024)

Population pharmacokinetics of imetelstat, a first‐in‐class oligonucleotide telomerase inhibitor

  • Mario González‐Sales,
  • Ashley L. Lennox,
  • Fei Huang,
  • Chandra Pamulapati,
  • Ying Wan,
  • Libo Sun,
  • Tymara Berry,
  • Melissa Kelly Behrs,
  • Faye Feller,
  • Peter N. Morcos

DOI
https://doi.org/10.1002/psp4.13160
Journal volume & issue
Vol. 13, no. 7
pp. 1264 – 1277

Abstract

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Abstract Imetelstat is a novel, first‐in‐class, oligonucleotide telomerase inhibitor in development for the treatment of hematologic malignancies including lower‐risk myelodysplastic syndromes and myelofibrosis. A nonlinear mixed‐effects model was developed to characterize the population pharmacokinetics of imetelstat and identify and quantify covariates that contribute to its pharmacokinetic variability. The model was developed using plasma concentrations from 7 clinical studies including 424 patients with solid tumors or hematologic malignancies who received single‐agent imetelstat via intravenous infusion at various dose levels (0.4–11.7 mg/kg) and schedules (every week to every 4 weeks). Covariate analysis included factors related to demographics, disease, laboratory results, renal and hepatic function, and antidrug antibodies. Imetelstat was described by a two‐compartment, nonlinear disposition model with saturable binding/distribution and dose‐ and time‐dependent elimination from the central compartment. Theory‐based allometric scaling for body weight was included in disposition parameters. The final covariates included sex, time, malignancy, and dose on clearance; malignancy and sex on volume of the central compartment; and malignancy and spleen volume on concentration of target. Clearance in females was modestly lower, resulting in nonclinically relevant increases in predicted exposure relative to males. No effects on imetelstat pharmacokinetics were identified for mild‐to‐moderate hepatic or renal impairment, age, race, and antidrug antibody status. All model parameters were estimated with adequate precision (relative standard error < 29%). Visual predictive checks confirmed the capacity of the model to describe the data. The analysis supports the imetelstat body‐weight–based dosing approach and lack of need for dose individualizations for imetelstat‐treated patients.