Predicting the Influence of Fat Food Intake on the Absorption and Systemic Exposure of Modern Small Drugs using ANDROMEDA by Prosilico Software

Introduction The ANDROMEDA software by Prosilico has previously been successfully applied and validated for predictions of absorption characteristics of small drugs in man. The effects of fat food on the gastrointestinal uptake and systemic exposure of drugs have, however, not yet been evaluated with the software.

Objective and Methodology The main objective was to use ANDROMEDA to predict area under the plasma concentration-time curve ratios in the fed (fat food) and fasted states (AUC_fed/AUC_fast) for small drugs marketed in 2021 and compare results with corresponding measured clinical estimates. A secondary aim was to make a similar evaluation for a set of selected older small drugs with no and significant food interaction.

Results 17 new drugs with observed AUC_fed/AUC_fast between 0.4 and 2.0 were found. In addition, 18 older drugs with low (0.5), moderate (1) and high (3.1-5.5) AUC_fed/AUC_fast were selected. Predicted AUC_fed/AUC_fast (for all drugs) had mean, median and maximum errors of 1.4-, 1.1- and 3.9-fold, respectively, and the predictive accuracy (correlation between predicted and observed AUC_fed/AUC_fast; Q²) was 0.35. For new small drugs, the Q² was 0.41. All 10 new drugs with AUC_fed/AUC_fast between 0.8 and 1.25 were predicted to have AUC_fed/AUC_fast between 0.6 and 1.5 and all 4 new drugs with AUC_fed/AUC_fast<1 were predicted to have AUC_fed/AUC_fast<1.05. Every predicted value ≥1.5 corresponded to a clinically significant food-drug interaction (AUC_fed/AUC_fast≥1.25).

Conclusion The results validate ANDROMEDA for prediction of fat food-drug interaction size for small drugs in man. Major advantages with the methodology include that results are produced directly from molecular structure and oral dose and an adequate level of predictive accuracy.