Obtaining pharmacokinetic population models using a genetic algorithm approach

Oscar Montiel; J. M. Cornejo; Carlos Sepúlveda; Roberto Sepúlveda

doi:10.1007/978-3-319-17747-2_24

Obtaining pharmacokinetic population models using a genetic algorithm approach

Oscar Montiel, J. M. Cornejo, Carlos Sepúlveda, Roberto Sepúlveda

Research output: Contribution to journal › Article › peer-review

Abstract

Nonlinear mixed effect model is the most used technique when developing a pharmacokinetic population model (PopPK), the characterization of a drug disposition into the body and taking decisions related to the dose adjustments. The covariate model is used to establish a relationship between the model parameters and the characteristics of the patients, and it helps to explain sources of variability in the PopPK. A known problem in the development of a covariate model is to decide which covariates should or should not be included in the model. In this work, a genetic algorithm (GA) was used to decide which covariates contribute in a major degree prediction of the variability in a PopPK model.

Original language	English
Pages (from-to)	305-317
Number of pages	13
Journal	Studies in Computational Intelligence
Volume	601
DOIs	https://doi.org/10.1007/978-3-319-17747-2_24
State	Published - 2015
Externally published	Yes

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abstract = "Nonlinear mixed effect model is the most used technique when developing a pharmacokinetic population model (PopPK), the characterization of a drug disposition into the body and taking decisions related to the dose adjustments. The covariate model is used to establish a relationship between the model parameters and the characteristics of the patients, and it helps to explain sources of variability in the PopPK. A known problem in the development of a covariate model is to decide which covariates should or should not be included in the model. In this work, a genetic algorithm (GA) was used to decide which covariates contribute in a major degree prediction of the variability in a PopPK model.",

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AU - Sepúlveda, Carlos

AU - Sepúlveda, Roberto

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AB - Nonlinear mixed effect model is the most used technique when developing a pharmacokinetic population model (PopPK), the characterization of a drug disposition into the body and taking decisions related to the dose adjustments. The covariate model is used to establish a relationship between the model parameters and the characteristics of the patients, and it helps to explain sources of variability in the PopPK. A known problem in the development of a covariate model is to decide which covariates should or should not be included in the model. In this work, a genetic algorithm (GA) was used to decide which covariates contribute in a major degree prediction of the variability in a PopPK model.

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JO - Studies in Computational Intelligence

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ER -

Obtaining pharmacokinetic population models using a genetic algorithm approach

Abstract

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