The oral route of administration is the most widely used mode of drug administration due to advantages such as the convenience of oral drug administration, patient choice, cost-effectiveness, and ease of generating oral dosage forms on a large scale. How effectively an oral drug is absorbed and made accessible to the target organ depends on a variety of factors. Poor absorption from the absorption site, excessive metabolism in the gut and liver, and pharmacokinetic drug-drug (PK-DDI) interactions can all contribute to inadequate therapy. The PK-DDI may result in greater than anticipated bioavailability and toxicity due to irreversible enzyme inhibition including time-dependent inactivation (TDI) of the intestinal enzymes.There are different in vitro models available to predict the fraction escaping gut metabolism (Fg), which is a major determinant of intestinal bioavailability. On the other hand, using pre-clinical species, Fg can be extrapolated in humans using allometric scaling, but there has been significant discordance due to the variable intestinal metabolism in humans vs. pre-clinical species. A number of absorption models have been developed over the years to predict oral drug absorption, and intestinal TDI can be incorporated into many of those models. In this study, the continuous intestinal absorption model has been refined, including the intestinal metabolism model, to predict the oral absorption of midazolam and nicardipine in both humans and rats. This absorption model was also used to predict the Fg of these drugs in those two species. The in vitro metabolic characteristics of the model drugs were investigated using both human and rat microsomes. The kinetic profiles of their metabolic conversion in rats and humans were developed using numerical techniques. The continuous absorption model explains how drug concentration changes with time and distance. A physiologically based pharmacokinetic (PBPK) model describes the intestine. The physiological inputs to the model, as well as the structure of the gastrointestinal tract, vary depending on the species. Rats and humans have different lengths of the small intestine's regions, such as the jejunum, and absorptive surface area amplifiers, such as the villi and microvilli. Along with the metabolic characteristics established through in vitro metabolic investigations, physiological aspects (applied to both rats and humans) and physicochemical drug characteristics were also added to the model. To estimate the absorption characteristics of midazolam and nicardipine, this model was further connected to the traditional compartmental model that represents the rest of the body. Chapter one details the background and importance concerning this project, along with the hypothesis and goals. Chapter two involves developing and validating bioanalytical methods for the drugs of interest. Chapters three and four detail the in vitro metabolic studies in rat and human microsomes (both intestinal and liver). Chapter five represents the TDI studies which were finally excluded from the absorption modeling in this thesis. Finally, chapter six illustrates the prediction of the oral PK profile of midazolam and nicardipine in rats and humans, rendering predicted values of Fg of these drugs in both species. Finally, chapter seven presents the significance, summary, and some directions to take this research further down the future. / Pharmaceutical Sciences

How can we model global phenomenon based on local interactions? Agent-Based (AB) models are local rule-based discrete method that can be used to simulate complex interactions of many agents. Unfortunately, the relative ease of implementing the computational model is often counter-balanced by the difficulty of performing rigorous analysis to determine emergent behaviors. Calculating existence of fixed points and their stability is not tractable from an analytical perspective and can become computationally expensive, involving potentially millions of simulations. To construct meaningful analysis, we need to create a framework to approximate the emergent, global behavior. Our research has been devoted to developing a framework for approximating AB models that move via random walks and undergo state transitions. First, we developed a general method to estimate the density of agents in each state for AB models whose state transitions are caused by neighborhood interactions between agents. Second, we extended previous random walk models of instantaneous state changes by adding a cumulative memory effect. In this way, our research seeks to answer how memory properties can also be incorporated into continuum models, especially when the memory properties effect state changes on the agents. The state transitions in this type of AB model is primarily from the agents’ interaction with their environment. These modeling frameworks will be generally applicable to many areas and can be easily extended.