Abstract More than 40% of marketed drugs and about 90% of drugs in development pipelines suffer from poor aqueous solubility and associated low bioavailability. Food, and lipids in particular, can significantly enhance the bioavailability of such drugs. This “food effect” could be exploited by developing lipid- and food-based formulations that demonstrate enhanced efficiency absorption, and as a result can be designed at a reduced drug dose while maintaining the same systemic exposure. Notably, using food components as formulation excipients would also mitigate food effects on bioavailability, thus allowing patients to take these medications irrespective of food, reducing the complexity of medication regiments, and ultimately addressing the significant issue of low patient adherence. However, lipid and food use in oral drug delivery is limited, in part, due to lack of ability to predict a priori lipid function in the GI tract and its effect on drug absorption. Our team has developed an algorithm that can predict the impact of food quantity and composition on drug absorption and bioavailability from a mechanistic point of view. Specifically, our algorithm considers multiple parallel, dynamic processes (drug dissolution, lipid and protein digestion, drug partitioning in colloids, absorption) to quantitatively predict the impact of food-associated lipids and proteins on oral bioavailability. This approach offers tremendous value by enabling rational quantitative guidance in developing improved dosage forms using lipids and other food ingredients as formulation excipients. In this project, we aim to develop novel formulations of a poorly bioavailable oral marketed drug that is known to be significantly impacted by food and is restricted to be taken only after a meal. The novel dosage forms will demonstrate enhanced capabilities in that they can be administered at a lower dose for the same therapeutic effect and administration with or without food will not impact bioavailability. Development of these formulations will demonstrate the practical application of our algorithm to improve oral delivery of poorly bioavailable drugs by exploiting the food effect. In the first aim, the existing algorithm will be adapted to predict drug pharmacokinetics after administration of an aqueous lipid/protein emulsion-based delivery vehicle. Kinetic parameters will be measured in vitro and used as model input parameters to inform selection of the most optimal drug dose and lipid-protein mixture composition that is bioequivalent to the marketed formulation. In the second aim, the modeling framework will be employed to select a lipid-surfactant-cosolvent system that can be administered as a lipid-based formulation inside a capsule. Formulation parameters (e.g., drug dose, excipient composition) will be optimized to inform development of a formulation that is bioequivalent to the marketed dosage form. Bioequivalence among all formulations will be demonstrated via pharmaco...