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

Abstract Introduction The ANDROMEDA software by Prosilico has previously been successfully applied and validated for predictions of absorption characteristics of small drugs in man. The influence 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 (AUCfed/AUCfast) for small drugs (including those marketed in 2021) and compare results with corresponding measured clinical estimates. Actual dose sizes were considered. Another objective was to compare the performance of ANDROMEDAvsphysiologically based pharmacokinetic (PBPK) modelling and simulations by The Food Effect PBPK IQ Working Group. PBPK results generated using Simcyp and GastroPlus software were based on various physicochemical,in vitroandin vivodata and a decision tree for model verification and optimization.Results and Discussion 63 drugs, including 17 new drugs, with observed AUCfed/AUCfastbetween 0.2 and 5.5 were found and used for this evaluation. Predicted AUCfed/AUCfasthad mean and maximum errors of 1.5- and 4.1-fold, respectively, and the predictive accuracy (correlation between predicted and observed AUCfed/AUCfast; Q2) was 0.3. 14 % of predictions had >2-fold error. For 72 % of drugs, food interaction class was correctly predicted. The level of predictive accuracy was overall similar to results obtained with PBPK modelling and simulations, however, with lower maximum error and higher compound coverage. With PBPK models, maximum simulation error was 7.7-fold and 3 highly lipophilic compounds were not possible to simulate.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 prediction results are produced directly from molecular structure and oral dose and are similar to PBPK-simulation results obtained usingin vitroand clinical data. Furthermore, ANDROMEDA showed lower maximum errors and wider compound range..

Medienart:	Preprint

Erscheinungsjahr:	2023
Erschienen:	2023

Enthalten in:	bioRxiv.org - (2023) vom: 28. Dez. Zur Gesamtaufnahme - year:2023

Sprache:	Englisch

Beteiligte Personen:	Fagerholm, Urban [VerfasserIn] Hellberg, Sven [VerfasserIn] Alvarsson, Jonathan [VerfasserIn] Spjuth, Ola [VerfasserIn]

Links:	Volltext [kostenfrei]

Themen:	570 Biology

doi:	10.1101/2022.12.05.519072

funding:
Förderinstitution / Projekttitel:

PPN (Katalog-ID):	XBI038119188