Bal, Gobardhan (2026) Evaluation of food effects on two anticancer drugs in humans: Application of physiologically based pharmacokinetic modeling as a surrogate strategy to minimize In-Vivo studies in drug development. Pharmacological Research - Reports, 5. ISSN 2950-2004

Abstract

Purpose
In oral drug delivery system, food may influence the effectiveness of the drug by modulating its bioavailability. Understanding these interactions between food and drugs is crucial during drug development. However, the conventional approaches used to identify them are expensive and time-consuming clinical trials, which are often impractical. The objective of this study is to address these challenges by leveraging physiologically based pharmacokinetic(PBPK) models as efficient in-silico tools to predict food effects using significantly less time and resources.
Methods
This work focused on developing and validating PBPK models of two low solubility anticancer drugs, Alectinib and Acalabrutinib, utilizing minimal in-vitro characterization data available at the early stage of drug development to demonstrate successful prediction of food effect. The models were developed for healthy humans incorporating drug-specific physicochemical properties, in-vitro characterization data, and physiological parameters of the gastrointestinal tract under both fasted and fed conditions.
Results
The prediction accuracy of the developed models was validated against the observed clinical data and further used for virtual population simulation to predict the food effect. The model validation parameters met the 2-fold error limit criteria. The predicted food effect data revealed that, despite low solubility, Alectinib exhibited a significant positive food effect, while Acalabrutinib showed no clinically relevant impact, consistent with the observed clinical data.
Conclusion
This work underscores the significance of the in-silico modeling and simulation approach in predicting the food effect of orally administered drugs, which could be used to minimize or optimize time-extensive and cost-expensive clinical trials in drug development.

Item Type:	Article
Date Deposited:	27 Jan 2026 00:45
Last Modified:	27 Jan 2026 00:45
URI:	https://oak.novartis.com/id/eprint/53064