Bruno, Christopher D.2019-03-262016-052016-06-222016http://nrs.harvard.edu/urn-3:HUL.InstRepos:38811449Drug discovery and development is a long, costly process that could become more efficient if pre-clinical exploration of drugs was more thorough and accurate. In order to provide pre-clinical insight into drug absorption, distribution, metabolism and elimination (ADME), as well as other behavioral patterns and dosing, we explore a physiologically-based pharmacokinetic model that incorporates an algorithm for predicting tissue:blood partition coefficients. Methods for predicting necessary parameters using in vitro and other laboratory techniques are also explored. The model was then used to simulate 150 person single-dose trials for five drugs (3 bases, 1 acid, 1 neutral) and assessed based on its ability to recreate observed C_max and AUC data. The model's accuracy ranged from predicting observed C_max within a standard deviation to only predicting 2.9% of the reported C_max, with similar results for AUC data. Overall, this model seems useful seems limited but useful for understanding general trends in drug ADME and dosing.application/pdfenBiology, PhysiologyBiology, MolecularThesis or Dissertation2019-03-260000-0003-2533-2960