Baron, Kyle Thomas2011-01-262011-01-262010-10https://hdl.handle.net/11299/99324University of Minnesota Ph.D. dissertation. October 2010. Major: Social, Administrative, and Clinical Pharmacy. Advisor: Dr. Richard Brundage. 1 computer file (PDF); xi, 165 pages, appendix A. Ill. (some col.)The first goal of this research was to develop models describing pharmacokinetics and pharmacodynamics of fludarabine in a patient population undergoing nonmyeloablative hematopoietic stem cell transplantation. The second goal was to leverage model information to identify fludarabine doses that are most likely to achieve optimal outcomes after transplant. Datasets consisting of intensively sampled F-ara-A plasma concentrations after approximately 40 mg/m2 fludarabine as well as outcome data (treatment-related mortality, maximum acute graft-versus-host disease grade, and neutrophil engraftment) were available at the start of the modeling work. Population pharmacokinetic models were built using NONMEM. Covariate models for pharmacokinetic parameters were derived, including a model for the typical value of clearance in the population as a function of weight, creatinine clearance, and comorbidity score. Bayesian generalized linear models linking F-ara-A exposure to outcome probabilities were fit using OpenBUGS software. Both models were evaluated using predictive model checking methods. Fludarabine doses were optimized with respect to individual outcomes by finding the posterior probability that a certain dose would meet specific criteria defining treatment "success". Doses were optimized simultaneously across all three outcomes using a utility index defined as the product of the individual outcome success probabilities. In general, the results recommend a reduction of fludarabine doses to optimize outcomes after hematopoietic stem cell transplantation.en-USExposure-response modelingFludarabinePharmacometricsStem cell transplantationSocial, Administrative, and Clinical PharmacyThesis or Dissertation