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A Bayesian Hierarchical Model for Studying Inter-Occasion and Inter-Subject Variability in Pharmacokinetics

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2011, PhD, University of Cincinnati, Arts and Sciences: Mathematical Sciences.

This dissertation includes two parts: developing a new model for individual pharmacokinetics (PK) and applying a Bayesian three-stage hierarchical model to population PK. As to individual PK, the standard methodology is compartment modeling characterized by physiological mechanisms. Parameters in individual PK are estimated based on data from a single individual. In the individual PK part, the relationship between drug concentration and time for an individual was modeled, and the kinetic parameters for an individual were characterized and quantified. Specifically, a piecewise absorption model without physiological compartment mechanisms was developed and applied for Mycophenolic acid (MPA) data that does not obey a one compartment first-order absorption pattern.

In the second part of this dissertation, a Bayesian three-stage hierarchical model was applied to population PK using simulated multi-occasion PK data with both inter-individual variability (IIV) and inter-occasion variability (IOV). This Bayesian approach was applied to three PK models. First, a PK model with independent IOV was studied, and different variances at different occasions were estimated. Second, a PK model with multivariate covariates and correlated and constrained IOV was studied, and unequal constrains in the variance matrix was modeled. Third, a PK model with arbitrary IOV was studied, and four inverse Whishart priors for IOV with different scale matrices were investigated. Based on the result and analysis, a recommendation of choosing the prior distribution was made according to whether or not a reliable source of the covariance matrix exists. For all population PK models, Gibbs sampling and Metropolis-Hasting algorithm were implemented using SAS IML to generate samples from posterior distributions.

Siva Sivaganesan, PhD (Committee Chair)
James Deddens, PhD (Committee Member)
Seongho Song, PhD (Committee Member)
Paul Horn, PhD (Committee Member)
151 p.

Recommended Citations

Citations

  • Li, X. (2011). A Bayesian Hierarchical Model for Studying Inter-Occasion and Inter-Subject Variability in Pharmacokinetics [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1296592410

    APA Style (7th edition)

  • Li, Xia. A Bayesian Hierarchical Model for Studying Inter-Occasion and Inter-Subject Variability in Pharmacokinetics. 2011. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1296592410.

    MLA Style (8th edition)

  • Li, Xia. "A Bayesian Hierarchical Model for Studying Inter-Occasion and Inter-Subject Variability in Pharmacokinetics." Doctoral dissertation, University of Cincinnati, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1296592410

    Chicago Manual of Style (17th edition)