(200ak) Importance of the Reaction Kinetics of Drug-Bile Micelle Formation in Oral-Drug Absorption Modeling
- Conference: AIChE Annual Meeting
- Year: 2018
- Proceeding: 2018 AIChE Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
- Time: Monday, October 29, 2018 - 3:30pm-5:00pm
The formation/dissociation of drug-bile conjugates happen as reversible reactions, which can be represented as a set of coupled differential equations describing the reaction kinetics. Previously-developed models typically assume that equilibrium between free drug and drug-bile micelles is achieved instantaneously, i.e., infinitely high forward/backward reaction rates. In the present work, this instantaneous-equilibrium assumption is relaxed and the effects of finite rate kinetics of drug-bile micelle formation/dissociation are examined. Using a model-drug molecule (dipyridamole), the set of differential equations incorporating finite drug-bile reaction rates was developed and applied to a setup for in-vitro flux experiments. In combination with these in-vitro flux experiments, the model was used to estimate the forward/backward reaction rate constants for the association/dissociation of drug to bile micelles. Interestingly, it is seen that the reaction rates are sufficiently low that the system deviates substantially from the assumption of instantaneous equilibrium. Therefore, the finite nature of the reaction rates noticeably impacts the absorption rate, hence, the performance of the drug product.
To improve upon the forward/backward reaction-rate estimation method, a second, more detailed model is introduced which accounts for the presence of aqueous boundary layers near the membrane surfaces of the in-vitro experimental setup. This updated model will allow for more accurate determination of the reaction rate constants and, subsequently, their impact on absorption. Establishing the importance of fundamental drug-bile interactions, and subsequent implementation of these mechanisms in oral-absorption software, will aid the development of comprehensive models that can drive rapid, low-cost drug development.