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PHARMACOKINETIC/PHARMACODYNAMIC MODELING FOR
GENETICALLY POLYMORPHIC POPULATIONS
by
Xiaoning Wang
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOMEDICAL ENGINEERING)
August 2007
Copyright 2007 Xiaoning Wang
Object Description
| Title | Pharmacokinetic/pharmacodynamic modeling for genetically polymorphic populations |
| Author | Wang, Xiaoning |
| Author email | xiaoninw@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Biomedical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2007-05-01 |
| Date submitted | 2007 |
| Restricted until | Unrestricted |
| Date published | 2007-06-05 |
| Advisor (committee chair) | D'Argenio, David Z. |
| Advisor (committee member) |
Schumitzky, Alan Khoo, Michael C.K. Conti, David V. |
| Abstract | This dissertation presents a model-based approach to study genetically polymorphic population as part of the drug development process. A nonlinear random effects model with a finite mixture structure is used to identify pharmacokinetic/pharmacodynamic phenotypes and quantify inter-subject variability. An EM algorithm for both maximum likelihood (ML) and maximum a posterior probability (MAP) estimation of the model is developed. It uses sampling-based methods to implement the expectation (E) step, followed by an analytically tractable maximization (M) step. A benefit of the approach is that no model linearization is performed and the estimation precision can be arbitrarily controlled by the sampling process. By classifying each individual in the population to the most likely subpopulation, this approach also provides a basis for further investigation on the genetic mechanism of the polymorphism and makes it possible for the subsequent genetics-based dose individualization.; Four simulations studies, with pharmacokinetic/pharmacodynamic models and various degrees of complexity for mixture model structures, illustrate the feasibility of the estimation approach and evaluate its performances. Some important features of the mixture modeling approach are investigated, including model selection, identifiability and potential singularity. Applications of the proposed approach to clinical trial datasets, as well as some extensions and further evaluations of the approach will be of interest for future investigation. |
| Keyword | finite mixture models; mixed effects models; pharmacokinetics/pharmacodynamics |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Type | texts |
| Legacy record ID | usctheses-m509 |
| Rights | Wang, Xiaoning |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Wang-20070605 |
| Archival file | uscthesesreloadpub_Volume44/etd-Wang-20070605.pdf |
Description
| Title | Page 1 |
| Full text | PHARMACOKINETIC/PHARMACODYNAMIC MODELING FOR GENETICALLY POLYMORPHIC POPULATIONS by Xiaoning Wang A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (BIOMEDICAL ENGINEERING) August 2007 Copyright 2007 Xiaoning Wang |
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