Literature DB >> 17497203

Weighted target interval stochastic control methods with global optimization and their applications in individualizing therapy.

Shaolin Ji1, Yingzhi Zeng, Ping Wu, Edmund Jon Deoon Lee.   

Abstract

Several improvements on the target interval stochastic control (TISC) method are addressed for individualizing therapy. In particular, a global optimization control strategy is implemented to obtain the optimal dosage regimen, and weighting functions are introduced to balance the drug efficacy and the risk of toxicity. Since general guidance is often lacking in the determination of a weighting function, we introduce a systematic approach, i.e., the standard reference gamble method of medical decision theory, for the determination of the weighting function. The population model for the individualization of theophylline therapy reported by D'Argenio and Katz is applied in this research. The present method of the integration of weighting functions and global optimal strategy offer an effective and safe means to balance the drug efficacy and risk of toxicity. In addition, it also achieves better accuracy than the existing TISC method which uses a local optimal strategy.

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Year:  2007        PMID: 17497203     DOI: 10.1007/s10928-007-9054-4

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.410


  7 in total

1.  Achieving target goals most precisely using nonparametric compartmental models and "multiple model" design of dosage regimens.

Authors:  R Jelliffe; D Bayard; M Milman; M Van Guilder; A Schumitzky
Journal:  Ther Drug Monit       Date:  2000-06       Impact factor: 3.681

2.  Sampling schedule design towards optimal drug monitoring for individualizing therapy.

Authors:  Shaolin Ji; Yingzhi Zeng; Ping Wu; Edmund Jon Deoon Lee
Journal:  Comput Methods Programs Biomed       Date:  2005-10       Impact factor: 5.428

3.  Modeling INR data to predict maintenance fluindione dosage.

Authors:  E Comets; F Mentré; F Pousset; B Diquet; G Montalescot; A Ankri; A Mallet; P Lechat
Journal:  Ther Drug Monit       Date:  1998-12       Impact factor: 3.681

4.  An application of Bayesian population pharmacokinetic/pharmacodynamic models to dose recommendation.

Authors:  J Wakefield; A Racine-Poon
Journal:  Stat Med       Date:  1995 May 15-30       Impact factor: 2.373

5.  Nonparametric estimation of population characteristics of the kinetics of lithium from observational and experimental data: individualization of chronic dosing regimen using a new Bayesian approach.

Authors:  N Taright; F Mentré; A Mallet; R Jouvent
Journal:  Ther Drug Monit       Date:  1994-06       Impact factor: 3.681

Review 6.  An efficient control strategy for dosage regimens.

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

Review 7.  Model-based, goal-oriented, individualised drug therapy. Linkage of population modelling, new 'multiple model' dosage design, bayesian feedback and individualised target goals.

Authors:  R W Jelliffe; A Schumitzky; D Bayard; M Milman; M Van Guilder; X Wang; F Jiang; X Barbaut; P Maire
Journal:  Clin Pharmacokinet       Date:  1998-01       Impact factor: 6.447

  7 in total

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