Literature DB >> 7473080

Comparison of some control strategies for three-compartment PK/PD models.

C Hu1, W S Lovejoy, S L Shafer.   

Abstract

In drug therapy, effective dosage strategies are needed to maintain target drug effects. The relationship between drug dose and drug effect is often described by pharmacokinetic/pharmacodynamic (PK/PD) models where typically the PK model has a multicompartment form and the PD model is the sigmoidal Emax model. The parameters in the PK/PD model are generally unknown in the individual patient, although prior knowledge may be available and can be updated after measurements of drug effect are taken during the therapy. This fact, together with the complexity of the PK/PD model, makes the control problem complex. This paper investigates several control strategies in the framework of a three-compartment PK model plus an effect site with a PD model. Using computer simulations under different assumptions, we show that a MAP (maximum a posteriori) Bayesian type of strategy is effective, nevertheless in high-risk situations a stochastic control strategy hedging against estimation errors provides better performance at computational cost.

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Mesh:

Year:  1994        PMID: 7473080     DOI: 10.1007/bf02353793

Source DB:  PubMed          Journal:  J Pharmacokinet Biopharm        ISSN: 0090-466X


  13 in total

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Review 5.  An efficient control strategy for dosage regimens.

Authors:  C Hu; W S Lovejoy; S L Shafer
Journal:  J Pharmacokinet Biopharm       Date:  1994-02

6.  Rapid prediction of individual dosage requirements for lignocaine.

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7.  Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine.

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8.  Targeting the systemic exposure of teniposide in the population and the individual using a stochastic therapeutic objective.

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Journal:  J Pharmacokinet Biopharm       Date:  1993-04

9.  Computer-assisted drug assay interpretation based on Bayesian estimation of individual pharmacokinetics: application to lidocaine.

Authors:  S Vozeh; R Hillman; M Wandell; T Ludden; L Sheiner
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10.  Bayesian forecasting improves the prediction of intraoperative plasma concentrations of alfentanil.

Authors:  P O Maitre; D R Stanski
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  1 in total

1.  Experiment design for nonparametric models based on minimizing Bayes Risk: application to voriconazole¹.

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Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-12-01       Impact factor: 2.745

  1 in total

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