A semimechanistic population pharmacokinetic and pharmacodynamic model incorporating autoinduction for the dose justification of TAS-114

Hikari Araki, Toru Takenaka, Koichi Takahashi, Fumiaki Yamashita, Kazuaki Matsuoka, Kunihiro Yoshisue, Ichiro Ieiri

Research output: Contribution to journalArticlepeer-review

Abstract

TAS-114 is a dual deoxyuridine triphosphatase (dUTPase) and dihydropyrimidine dehydrogenase (DPD) inhibitor expected to widen the therapeutic index of capecitabine. Its maximum tolerated dose (MTD) was determined from a safety perspective in a combination study with capecitabine; however, its inhibitory effects on DPD activity were not assessed in the study. The dose justification to select its MTD as the recommended dose in terms of DPD inhibition has been required, but the autoinduction profile of TAS-114 made it difficult. To this end, an approach using a population pharmacokinetic (PPK)/pharmacodynamic (PD) model incorporating autoinduction was planned; however, the utility of this approach in the dose justification has not been reported. Thus, the aim of this study was to demonstrate the utility of a PPK/PD model incorporating autoinduction in the dose justification via a case study of TAS-114. Plasma concentrations of TAS-114 from 185 subjects and those of the endogenous DPD substrate uracil from 24 subjects were used. A two-compartment model with first-order absorption with lag time and an enzyme turnover model were selected for the pharmacokinetic (PK) model. Moreover, an indirect response model was selected for the PD model to capture the changes in plasma uracil concentrations. Model-based simulations provided the dose justification that DPD inhibition by TAS-114 reached a plateau level at the MTD, whereas exposures of TAS-114 increased dose dependently. Thus, the utility of a PPK/PD model incorporating autoinduction in the dose justification was demonstrated via this case study of TAS-114.

Original languageEnglish
JournalCPT: Pharmacometrics and Systems Pharmacology
DOIs
Publication statusAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Pharmacology (medical)

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