(T1530-01-02) Biopharmaceutical Modeling of Food Effect – Exploring a Role for Dietary Fat

Purpose: In preclinical drug discovery, simple fraction absorbed calculators are invaluable tools to better understand the potential limitations to drug absorption and how different formulation approaches may address them [1].  For many poorly soluble compounds, bile micelle solubilization plays an important role in dissolution and absorption and is relatively well defined in these models [2].  In the fed state there is the addition of lipid digestion products whose impact is not necessarily fully described by bile micelles alone.  It is known that the fat content in the meals given with a medication effect the extent of food effect observed, however these simple models lack a mechanism to include the impact of fat content in the gut on drug absorption. Here, we investigate a potential mechanism by which dietary fat from meals may contribute to enhanced absorption along a similar framework as the particle drift effect described previously for drug particle movement into the UWL [3]. For this work, we relied a wealth of published food effect data for a range of different marketed drugs and compare multiple absorption modeling approaches to investigate how each correlate to the observed data [4].

Methods: We investigated three different absorption models to compare their relative predictions of food effect for a range of published compounds. The first model was based on a previously published analytical solution with a steady state approximation for drug concertation where food effect was incorporated into the solubility term used and the fraction of drug held in bile micelles. The second model built on the first, only now incorporating changes to bile micelle structure in the fed state, which increase the diffusivity of the bile micelle. In the third model, we propose a novel mechanism to incorporate the fat content from diet as an additional set of particles that can accumulate in the mucus and act to reduce the effective thickness of the UWL (Figure 1). The impact of this new particle population on UWL thickness is scaled based on the lipophilicity of the molecule being modeled. Using published data for 20 model compounds, along with detailed food effect data for select compounds across broad dose ranges and in different fed state conditions, we evaluated each model for their predictive food effect [4].

Results: Predicting food effect using simple fraction absorbed calculators was relatively successful. For the first model, many compounds with reported positive food effect were able to be identified in the model, however the extent of food effect was not reflected well in the model output. For the second model, the extent of food effect was more pronounced for some compounds, though still lacking for many compounds with the highest reported food effect. The third model demonstrated the best fit to the reported data, providing an excellent fit for the reported extent of food effect for most of the compounds investigated (Figure 2). These models were further evaluated by testing their prediction of food effect for a range of dose levels of select compounds compared to reported values [5].

Conclusion: Incorporating the impact of dietary fat within absorption models can provide additional sensitivity to food effect and improve model predictions for the extent of positive food effect. The FDA suggested high fat meal contains at least 55 grams of fat, which is emulsified in the gut to generate a coarse emulsion that can last in the small intestine for multiple hours [5-7]. Viewing these lipid droplets in a similar framework as drug particles for their impact on the unstirred water layer, we can begin to incorporate their impact on drug absorption in a way that can account for the overall volume of lipid in the meal. This work presents the first effort that we are aware of that incorporates the lipid fraction of diet into an absorption model directly for its impact on the intestinal environment.

References: 1. Sugano, K. (2009). Introduction to computational oral absorption simulation. Expert Opinion on Drug Metabolism & Toxicology, 5(3), 259–293.
2. Sugano, K. (2009). Calculation of fraction of dose absorbed: Comparison between analytical solution based on one compartment steady state concentration approximation and dynamic seven compartment model. Chem-Bio Informatics Journal, 9, 75–93.
3. Sugano, K. (2010). Possible reduction of effective thickness of intestinal unstirred water layer by particle drifting effect. International Journal of Pharmaceutics, 387(1-2), 103–109.
4. Riedmaier, A. E., DeMent, K., Huckle, J., Bransford, P., Stillhart, C., Lloyd, R., Alluri, R., Basu, S., Chen, Y., Dhamankar, V., Dodd, S., Kulkarni, P., Olivares-Morales, A., Peng, C.-C., Pepin, X., Ren, X., Tran, T., Tistaert, C., Heimbach, T., … Parrott, N. (2020). Use of physiologically based pharmacokinetic (PBPK) modeling for predicting drug-food interactions: An industry perspective. The AAPS Journal, 22(6).
5. Armand, M., Borel, P., Dubois, C., Senft, M., Peyrot, J., Salducci, J., Lafont, H. Lairon, D. (1994). Characterization of emulsions and lipolysis of dietary lipids in the human stomach. American Journal of Physiology-Gastrointestinal and Liver Physiology, 266(3).
6. Armand, M., Borel, P., Pasquier, B., Dubois, C., Senft, M., Andre, M., Peyrot, J., Salducci, J., Lairon, D. (1996). Physicochemical characteristics of emulsions during fat digestion in human stomach and duodenum. American Journal of Physiology-Gastrointestinal and Liver Physiology, 271(1).
7. U.S. Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research (CDER). (2019). Assessing the Effects of Food on Drugs in INDs and NDAs — Clinical Pharmacology Considerations. FDA.

Figure 1. Schematic of UWL thickness impact of different particle populations including both drug particles and dietary lipid droplets.



Figure 2. Comparison of three different absorption models for their predicted food effect compared to the reported Fed/Fasted AUC ratio.