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Integration of Mechanisms Affecting ...

Sharma, Sheena.

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Integration of Mechanisms Affecting the Activity of Drug Metabolizing Enzymes and Transporters to Predict Variability in Oral Drug Absorption.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Integration of Mechanisms Affecting the Activity of Drug Metabolizing Enzymes and Transporters to Predict Variability in Oral Drug Absorption./
作者:	Sharma, Sheena.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:	201 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
Contained By:	Dissertations Abstracts International85-01B.
標題:	Pharmaceutical sciences. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30312510
ISBN:	9798379911140

Integration of Mechanisms Affecting the Activity of Drug Metabolizing Enzymes and Transporters to Predict Variability in Oral Drug Absorption.
Sharma, Sheena.

Integration of Mechanisms Affecting the Activity of Drug Metabolizing Enzymes and Transporters to Predict Variability in Oral Drug Absorption. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 201 p.

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

Thesis (Ph.D.)--Washington State University, 2023.

.

The oral route of drug administration is the most convenient method of drug delivery, but it is associated with variable pharmacokinetics (PK). Oral drug bioavailability can be affected by changes in physicochemical properties and gastrointestinal physiology. For example, formulation factors, food, drug-drug interactions (DDIs), genetic polymorphisms, sex, and disease can alter the abundance of drug metabolizing enzymes and transporters (DMETs), which can subsequently impact oral bioavailability. However, the underlying mechanisms of variable oral bioavailability, particularly the complex interplay among individual factors, are not fully understood. The lack of mechanistic understanding limits the prediction of oral drug bioavailability using mechanistic approaches such as physiologically based PK (PBPK) modeling. This dissertation focuses on characterizing the mechanisms associated with variability in oral drug bioavailability and predicting the oral PK using PBPK modeling.The significance, knowledge gaps, hypothesis, and specific aims of the dissertation work are outlined in Chapter 1. Chapter 2 focuses on investigating the role of a polymorphic intestinal enzyme, UDP-glucuronosyltransferase 2B17 (UGT2B17), in the first-pass metabolism and oral bioavailability of an investigational male contraceptive (dimethandrolone, DMA) in humans. We found that UGT2B17-mediated high intestinal first-pass metabolism is the key mechanism underlying variable DMA bioavailability. In Chapter 3, first, clinically relevant DMET proteins were quantified in the liver and different intestinal segments of Sprague Dawley rats. The utility of DMET proteomics data was next demonstrated for predicting the systemic and tissue drug exposure of the model drug, digoxin. Chapter 4 evaluates the interplay among breast cancer resistance protein (Bcrp), sex, and the fed state in oral PK variability of furosemide, a well-studied clinical probe for renal organic anion transporter (OAT)-mediated DDIs. This is the first study to demonstrate a significant DDI between furosemide and a Bcrp inhibitor (novobiocin) using the rat model. Chapters 5 and 6 identify the effects of food-related factors on oral drug absorption using meta-analysis and artificial intelligence/machine learning approaches and highlight the role of prolonged gastric-emptying and increased blood and bile flow on the food effect.This dissertation work improves the understanding of key physiological mechanisms leading to variability in oral drug absorption, which has potential applications in drug development and clinical pharmacology. The proteomics and functional activity data generated are important for predicting species differences in metabolism and transport affecting oral drug bioavailability between rats and humans. It also establishes proteomics-informed PBPK modeling as a promising tool for predicting systemic and tissue drug concentrations.

ISBN: 9798379911140Subjects--Topical Terms:

3173021
Pharmaceutical sciences.
Subjects--Index Terms:

Artificial intelligence/machine learning

Integration of Mechanisms Affecting the Activity of Drug Metabolizing Enzymes and Transporters to Predict Variability in Oral Drug Absorption.
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