Journal of Pharmacokinetics and Biopharmaceutics

, Volume 26, Issue 1, pp 103–123 | Cite as

A Use of Monte Carlo Integration for Population Pharmacokinetics with Multivariate Population Distribution

  • Akifumi Yafune
  • Masato Takebe
  • Hiroyasu Ogata


This paper describes a use of Monte Carlo integration for population pharmacokinetics with multivariate population distribution. In the proposed approach, a multivariate lognormal distribution is assumed for a population distribution of pharmacokinetic (PK) parameters. The maximum likelihood method is employed to estimate the population means, variances, and correlation coefficients of the multivariate lognormal distribution. Instead of a first-order Taylor series approximation to a nonlinear PK model, the proposed approach employs a Monte Carlo integration for the multiple integral in maximizing the log likelihood function. Observations below the lower limit of detection, which are usually included in Phase 1 PK data, are also incorporated into the analysis. Applications are given to a simulated data set and an actual Phase 1 trial to show how the proposed approach works in practice.

Monte Carlo integration multivariate population distribution numerical approach phase 1 trial 


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Copyright information

© Plenum Publishing Corporation 1998

Authors and Affiliations

  • Akifumi Yafune
    • 1
    • 2
  • Masato Takebe
    • 1
  • Hiroyasu Ogata
    • 3
  1. 1.Department of Clinical PharmacologyBio-Iatric Center, the Kitasato InstituteTokyoJapan
  2. 2.Department of Pharmacoepidemiology, Faculty of MedicineUniversity of TokyoTokyoJapan
  3. 3.Department of PharmaceuticsMeiji College of PharmacyTokyoJapan

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