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Estimation of Population Pharmacokinetic Parameters Using a Genetic Algorithm

  • Carlos Sepúlveda
  • Oscar Montiel
  • José. M. Cornejo Bravo
  • Roberto Sepúlveda
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 667)

Abstract

Population pharmacokinetics (PopPK) models are used to characterize the behavior of a drug in a particular population. Construction of PopPK models requires the estimation of optimal PopPK parameters, which is a challenging task due to the characteristics of the PopPK database. Several estimation algorithms have been proposed for estimating PopPK parameters; however, the majority of these methods are based on maximum likelihood estimation methods that optimize the probability of observing data, given a model that requires the systematic computation of the first and second derivate of a multivariate likelihood function. This work presents a genetic algorithm for obtaining optimal PopPK parameters by directly optimizing the multivariate likelihood function avoiding the computation of the first and second derivate of the likelihood function.

Keywords

Population pharmacokinetic Mixed effects models Genetic algorithm 

Notes

Acknowledgments

We thank to Instituto Politécnico Nacional (IPN), to the Commission of Operation and Promotion of Academic Activities of IPN (COFAA), and the Mexican National Council of Science and Technology (CONACYT) for supporting our research activities.

References

  1. 1.
    Paul J. Williams, Ene I. Ette. The Role of Population Pharmacokinetics in Drug Development in Light of the Food and Drug Administration’s ‘Guidance for Industry: Population Pharmacokinetics’. Springer, (2000)Google Scholar
  2. 2.
    Lang Wu. Mixed Effects Models for Complex Data. CRC Press, (2010)Google Scholar
  3. 3.
    Bruce L. Bowerman, RichardT. O’Conell, Emily S. Murpheree, Experimental Design: Unified Concepts, Practical Applications, and Computer Implementation. Business Expert Press. (2015)Google Scholar
  4. 4.
    Joel S. Owen and Jill Fieldler-Kelly. Introduction to Population Pharmacokinetic/Pharmacodynamic Analysis with Nonlinear Mixed Effects Models. Wiley, (2014)Google Scholar
  5. 5.
    Ene I.Ette, Paul J. Williams. Pharmacometrics: the science of quantitative pharmacology (2007)Google Scholar
  6. 6.
    Marc Lavielle, Kevin Bleakley. Mixed Effects Models for the Population Approach: Models, Task, Methods and Tools. CRC Press, (2015)Google Scholar
  7. 7.
    Dan Simon. Evolutionary Optimization Algorithms: Biologically-Inspired and Population-Based Approaches to Computer Intelligence. Wiley. (2013)Google Scholar
  8. 8.
    Marie Davidian and David M. Giltinan. Nonlinear Models for Repeated Measurement Data, Chapman & Hall, (1995)Google Scholar
  9. 9.
    Johan Gabrielsson, Dan Weiner. Pharmacokinetic & Pharmacodynamic Data Analysis: Concepts and Applications. Apotekarsocieteten, (2006)Google Scholar
  10. 10.
    Seongho Kim, Lang Li. A novel global search algorithm for nonlinear mixed-effects models Springer Science+BusinessMedia, (2011)Google Scholar
  11. 11.
    Holland, J.H. Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press, (1975)Google Scholar
  12. 12.
    S.N. Sivanandam,S.N. Deepa. Introduction to Genetic Algorithms. Springer, (2008)Google Scholar
  13. 13.
    Chang Wook Ahn. Advances in Evolutionary Algorithms. Theory, Design and Practice. Springer, (2006)Google Scholar
  14. 14.
    A.E. Eiben, J.E. Smith, Introduction to Evolutionary Computing. Springer, (2003)Google Scholar
  15. 15.
    Robert Lowen and Alain Verschoren. Foundations of Generic Optimization. Springer, (2008)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Carlos Sepúlveda
    • 1
  • Oscar Montiel
    • 1
  • José. M. Cornejo Bravo
    • 2
  • Roberto Sepúlveda
    • 1
  1. 1.Instituto Politécnico NacionalCentro de Investigación y Desarrollo de Tecnología Digital (CITEDI-IPN)TijuanaMéxico
  2. 2.Facultad de Ciencias Químicas e IngenieríaUniversidad Autónoma de Baja California (UABC)TijuanaMéxico

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