Modeling Impact of Ingested Lipids on Orally Delivered Drug Dissolution

Introduction Ingested lipids could offer valuable opportunities for enabling oral drug delivery, as approximately 4070% of all new drug candidates have been estimated to have very poor water solubility and are expected to exhibit low bioavailability when orally dosed. For hydrophobic drug molecules, the dissolution process in water is likely the limiting step of overall oral absorption. Therefore, the influence of ingested lipids on oral absorption has been associated with complex and poorly characterized interactions between drugs and several colloidal structures, which are naturally present in the gastrointestinal fluids after food intake. In particular, emulsion droplets, micelles and vesicles influence dissolution kinetics, and they are able to maintain larger quantities of hydrophobic drugs in solution, increasing the solubilization power of the gastrointestinal (GI) tract contents. Furthermore, the distribution of drugs within oil, aqueous and micellar phases affects their absorption rate. However, despite the recognized capability of ingested lipids to impact several processes associated with the overall absorption of hydrophobic drugs, the fate of co-administered drugs remains unclear and unpredictable. The aim of this study is to quantitatively investigate and model the effects of ingested lipids on dissolution and partitioning of orally delivered drugs by means of updated in vitro models incorporating simulated intestinal fluids. Kinetics of drug dissolution and partitioning between colloidal phases (oil, micellar, aqueous) have been studied by high performance liquid chromatography (HPLC) and electron paramagnetic resonance (EPR), respectively. The latter is a non-invasive technique that has the capability of detecting and quantifying radicals acting as spin probes. Since EPR spectra are highly sensitive to changes in environment micropolarity and microviscosity, the relocation of a selected spin probe within different phases can be monitored in real-time and quantified.