Prediction of Human Intestinal Absorption
| dc.contributor.advisor | Yalkowsky, Samuel H. | en |
| dc.contributor.author | Patel, Raj B. | |
| dc.creator | Patel, Raj B. | en |
| dc.date.accessioned | 2017-06-28T21:01:22Z | |
| dc.date.available | 2017-06-28T21:01:22Z | |
| dc.date.issued | 2017 | |
| dc.identifier.uri | http://hdl.handle.net/10150/624487 | |
| dc.description.abstract | The proposed human intestinal absorption prediction model is applied to over 900 pharmaceuticals and has about 82.5% true prediction power. This study will provide a screening tool that can differentiate well absorbed and poorly absorbed drugs in the early stage of drug discovery and development. This model is based on fundamental physicochemical properties and can be applied to virtual compounds. The maximum well-absorbed dose (i.e., the maximum dose that will be more than 50 percent absorbed) calculated using this model can be utilized as a guideline for drug design, synthesis, and pre-clinical studies. | |
| dc.language.iso | en_US | en |
| dc.publisher | The University of Arizona. | en |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en |
| dc.subject | Aqueous Solubility | en |
| dc.subject | Dose | en |
| dc.subject | Human Intestinal Absorption| | en |
| dc.subject | Melting Point | en |
| dc.subject | Octanol-water Partition Coefficient | en |
| dc.subject | Predictive Modeling | en |
| dc.title | Prediction of Human Intestinal Absorption | en_US |
| dc.type | text | en |
| dc.type | Electronic Dissertation | en |
| thesis.degree.grantor | University of Arizona | en |
| thesis.degree.level | doctoral | en |
| dc.contributor.committeemember | Yalkowsky, Samuel H. | en |
| dc.contributor.committeemember | Myrdal, Paul B. | en |
| dc.contributor.committeemember | Mayersohn, Michael | en |
| dc.contributor.committeemember | Mansour, Heidi | en |
| dc.description.release | Release after 22-Dec-2017 | en |
| thesis.degree.discipline | Graduate College | en |
| thesis.degree.discipline | Pharmaceutical Sciences | en |
| thesis.degree.name | Ph.D. | en |
| refterms.dateFOA | 2017-12-22T00:00:00Z | |
| html.description.abstract | The proposed human intestinal absorption prediction model is applied to over 900 pharmaceuticals and has about 82.5% true prediction power. This study will provide a screening tool that can differentiate well absorbed and poorly absorbed drugs in the early stage of drug discovery and development. This model is based on fundamental physicochemical properties and can be applied to virtual compounds. The maximum well-absorbed dose (i.e., the maximum dose that will be more than 50 percent absorbed) calculated using this model can be utilized as a guideline for drug design, synthesis, and pre-clinical studies. |
