Drug Design, Development and Therapy (Feb 2020)

Contribution of Trough Concentration Data in the Evaluation of Multiple-Dose Pharmacokinetics for Drugs with Delayed Distributional Equilibrium and Long Half-Life

  • Choi S,
  • Jeon S,
  • Yim DS,
  • Han S

Journal volume & issue
Vol. Volume 14
pp. 811 – 821

Abstract

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Suein Choi,1,2 Sangil Jeon,3 Dong-Seok Yim,1,2 Seunghoon Han1,2 1Pharmacometrics Institute for Practical Education and Training (PIPET), College of Medicine, The Catholic University of Korea, Seoul, Korea; 2Department of Pharmacology, College of Medicine, The Catholic University of Korea, Seoul, Korea; 3Q-Fitter, Seoul, KoreaCorrespondence: Seunghoon HanDepartment of Pharmacology, College of Medicine, The Catholic University of Korea, 222, Banpo-Daero, Seocho-Gu, Seoul 06591, KoreaTel +82 2 2258 7326 Fax +82 2 2258 7876Email [email protected]: The performance of “trough sampling before reaching steady-state” and “serial sampling beyond the interval between steady-state” in a multiple-dose pharmacokinetic evaluation was compared. Drugs with long half-lives, following multi-compartment pharmacokinetics, and whose distribution-related characteristics are less likely to be assessed within one dosing interval are focused.Patients and methods: Amlodipine pharmacokinetic data were collected from a human pharmacology study performed in Seoul St. Mary’s Hospital (Seoul, Korea). Plasma concentration data until 144 hrs after a single administration was used. Nonlinear mixed-effects modeling was conducted to obtain the “true” model structure and pharmacokinetic parameter estimates. Then, stochastic simulation and estimation were performed using multiple-dose scenarios in various sampling strategies. Parameter accuracy and precision from each scenario were evaluated.Results: A two-compartment model with first-order absorption followed by zero-order absorption with a lag time then first-order elimination was chosen as the final model and used in the stochastic simulation and estimation. In terms of parameter precision, the scenario incorporating data only within one dosing interval showed the worst results (Vp/F = 313%, Q/F = 64.3%). Some scenarios including early trough samples yielded comparable outcomes (Vp/F = 18.4%, Q/F = 32.1%) to the extended full-PK sampling scenario (Vp/F = 15.9%, Q/F = 30.3%), which was the best case. The quality of distribution-related parameters was the major difference between scenarios.Conclusion: In multiple-dose studies on drugs with delayed distributional equilibrium, information from a few trough samples can augment the limit of serial sampling within the dosing interval for parameter estimation. With informative trough samples, extended hospitalization for serial sampling (until 3– 5 half-lives after the last dose), which is particularly problematic for long half-life drugs, may be avoided. Trough samples obtained at the beginning of the repeated dose were more effective for mixed-effects modeling.Keywords: pharmacokinetics, trough sampling, multiple-dose, stochastic simulation and estimation, NONMEM

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