Semiparametric mixed-effects analysis of PK/PD models using differential equations

Yi Wang, Kent M. Eskridge, Shunpu Zhang

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Motivated by the use of semiparametric nonlinear mixed-effects modeling on longitudinal data, we develop a new semiparametric modeling approach to address potential structural model misspecification for population pharmacokinetic/ pharmacodynamic (PK/PD) analysis. Specifically, we use a set of ordinary differential equations (ODEs) with form dx/dt = A(t)x + B(t) where B(t) is a nonparametric function that is estimated using penalized splines. The inclusion of a nonparametric function in the ODEs makes identification of structural model misspecification feasible by quantifying the model uncertainty and provides flexibility for accommodating possible structural model deficiencies. The resulting model will be implemented in a nonlinear mixed-effects modeling setup for population analysis. We illustrate the method with an application to cefamandole data and evaluate its performance through simulations.

Original languageEnglish (US)
Pages (from-to)443-463
Number of pages21
JournalJournal of Pharmacokinetics and Pharmacodynamics
Volume35
Issue number4
DOIs
StatePublished - Aug 1 2008

Fingerprint

Structural Models
Pharmacokinetics
Cefamandole
Population
Uncertainty

Keywords

  • Compartmental models
  • Mixed-effects modeling
  • Splines

ASJC Scopus subject areas

  • Pharmacology

Cite this

Semiparametric mixed-effects analysis of PK/PD models using differential equations. / Wang, Yi; Eskridge, Kent M.; Zhang, Shunpu.

In: Journal of Pharmacokinetics and Pharmacodynamics, Vol. 35, No. 4, 01.08.2008, p. 443-463.

Research output: Contribution to journalArticle

@article{0e414445dce9481ba6b7ebac1f89120c,
title = "Semiparametric mixed-effects analysis of PK/PD models using differential equations",
abstract = "Motivated by the use of semiparametric nonlinear mixed-effects modeling on longitudinal data, we develop a new semiparametric modeling approach to address potential structural model misspecification for population pharmacokinetic/ pharmacodynamic (PK/PD) analysis. Specifically, we use a set of ordinary differential equations (ODEs) with form dx/dt = A(t)x + B(t) where B(t) is a nonparametric function that is estimated using penalized splines. The inclusion of a nonparametric function in the ODEs makes identification of structural model misspecification feasible by quantifying the model uncertainty and provides flexibility for accommodating possible structural model deficiencies. The resulting model will be implemented in a nonlinear mixed-effects modeling setup for population analysis. We illustrate the method with an application to cefamandole data and evaluate its performance through simulations.",
keywords = "Compartmental models, Mixed-effects modeling, Splines",
author = "Yi Wang and Eskridge, {Kent M.} and Shunpu Zhang",
year = "2008",
month = "8",
day = "1",
doi = "10.1007/s10928-008-9096-2",
language = "English (US)",
volume = "35",
pages = "443--463",
journal = "Journal of Pharmacokinetics and Pharmacodynamics",
issn = "1567-567X",
publisher = "Springer New York",
number = "4",

}

TY - JOUR

T1 - Semiparametric mixed-effects analysis of PK/PD models using differential equations

AU - Wang, Yi

AU - Eskridge, Kent M.

AU - Zhang, Shunpu

PY - 2008/8/1

Y1 - 2008/8/1

N2 - Motivated by the use of semiparametric nonlinear mixed-effects modeling on longitudinal data, we develop a new semiparametric modeling approach to address potential structural model misspecification for population pharmacokinetic/ pharmacodynamic (PK/PD) analysis. Specifically, we use a set of ordinary differential equations (ODEs) with form dx/dt = A(t)x + B(t) where B(t) is a nonparametric function that is estimated using penalized splines. The inclusion of a nonparametric function in the ODEs makes identification of structural model misspecification feasible by quantifying the model uncertainty and provides flexibility for accommodating possible structural model deficiencies. The resulting model will be implemented in a nonlinear mixed-effects modeling setup for population analysis. We illustrate the method with an application to cefamandole data and evaluate its performance through simulations.

AB - Motivated by the use of semiparametric nonlinear mixed-effects modeling on longitudinal data, we develop a new semiparametric modeling approach to address potential structural model misspecification for population pharmacokinetic/ pharmacodynamic (PK/PD) analysis. Specifically, we use a set of ordinary differential equations (ODEs) with form dx/dt = A(t)x + B(t) where B(t) is a nonparametric function that is estimated using penalized splines. The inclusion of a nonparametric function in the ODEs makes identification of structural model misspecification feasible by quantifying the model uncertainty and provides flexibility for accommodating possible structural model deficiencies. The resulting model will be implemented in a nonlinear mixed-effects modeling setup for population analysis. We illustrate the method with an application to cefamandole data and evaluate its performance through simulations.

KW - Compartmental models

KW - Mixed-effects modeling

KW - Splines

UR - http://www.scopus.com/inward/record.url?scp=52549092939&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=52549092939&partnerID=8YFLogxK

U2 - 10.1007/s10928-008-9096-2

DO - 10.1007/s10928-008-9096-2

M3 - Article

C2 - 18781382

AN - SCOPUS:52549092939

VL - 35

SP - 443

EP - 463

JO - Journal of Pharmacokinetics and Pharmacodynamics

JF - Journal of Pharmacokinetics and Pharmacodynamics

SN - 1567-567X

IS - 4

ER -