Publication: Predictive Pharmacokinetic Modeling of Orally Administered Drugs
| dash.author.email | christopherbruno14@gmail.com | |
| dash.depositing.author | Bruno, Christopher D. | |
| dash.identifier.vireo | http://etds.lib.harvard.edu/college/admin/view/148 | |
| dash.license | LAA | |
| dc.contributor.author | Bruno, Christopher D. | |
| dc.date.accessioned | 2019-03-26T10:41:32Z | |
| dc.date.available | 2019-03-26T10:41:32Z | |
| dc.date.created | 2016-05 | |
| dc.date.issued | 2016-06-22 | |
| dc.date.submitted | 2016 | |
| dc.description.abstract | Drug 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. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.orcid | 0000-0003-2533-2960 | |
| dc.identifier.uri | http://nrs.harvard.edu/urn-3:HUL.InstRepos:38811449 | * |
| dc.language.iso | en | |
| dc.subject | Biology, Physiology | |
| dc.subject | Biology, Molecular | |
| dc.title | Predictive Pharmacokinetic Modeling of Orally Administered Drugs | |
| dc.type | Thesis or Dissertation | |
| dc.type.material | text | |
| dspace.entity.type | Publication | |
| oaire.licenseCondition | LAA | |
| thesis.degree.date | 2016 | |
| thesis.degree.grantor | Harvard College | |
| thesis.degree.level | Undergraduate | |
| thesis.degree.name | AB |