Abstract 856: Comparison of the effect of two EGFR-TKI in patients with EGFR-mutant lung adenocarcinoma using in silico clinical trials
Authors: Darré Hippolyte , Martin Bastien , Hammami Firas , Nativel Arnaud , Lefaudeux Diane , Toueg Raphaël , Duruisseaux Michaël , Palgen Jean-Louis , Masson Perrine , L'Hostis Adèle , Ceres Nicoletta , Monteiro Claudio 
Published: April 2023

Introduction: 16,4% of lung adenocarcinomas (LUAD) are presenting a mutation in the Epidermal Growth Factor Receptor (EGFR), as reported in the Epidemiological Strategy and Medical Economics database[1], resulting in its constitutive activation and leading to uncontrolled cell proliferation. While some tyrosine kinase inhibitors (TKIs) have been developed to target EGFR mutations, their efficacy is not long-lasting, due to the emergence of resistance mutations[2]. Based on in silico approaches, we investigate and compare the impact of two TKIs (1st and 3rd generation) on tumor size evolution and clinical outcome, depending on the target population.

Materials and Methods: We developed in Novadiscovery's jinkō platform a detailed mechanistic disease model of EGFR-mutant LUAD that predicts patients’ disease progression, based on their characteristics. We added on top of this disease model, a mechanistic physiologically-based pharmaco-kinetics model for each TKI drug, integrating their mechanisms of action. Publicly available data were used to calibrate the drug models and assess their credibility.We used the combination of the disease model with the two drug models to simulate clinical trials to compare the impact of both drugs on the course of the disease. Results:Both the 1st and 3rd generation TKI drug models can reproduce the pharmacokinetics in mice and humans. Combination of these models with the EGFR-mutant LUAD disease model is used to predict the tumor evolution in mice and the clinical outcome in humans. Differences in disease progression between treatments are observed according to the patients’ tumor mutational profiles.

Discussion and Conclusion: The knowledge based construction of this EGFR mutant LUAD disease and treatment model successfully reproduced publicly available real-world data and will be challenged to reproduce the results from the FLAURA trial for an additional step of validation. The credibility of the model thereby acquired is a first step in the use of the model to compare existing treatments to investigational treatments and further support innovative therapies development. As such, in silico approaches are a complementary and valuable tool to existing in vitro or in animal experiments, alongside with clinical trials performance.

References:

[1] Chouaid et al, TargOnc, 2021, https://doi.org/10.1007/s11523-021-00848-9.

[2] Vyse et al, Signal Transduction and Targeted Therapy, 2019 https://doi.org/10.1038/s41392-019-0038-9.

Citation Format: Hippolyte Darré, Bastien Martin, Firas Hammami, Arnaud Nativel, Diane Lefaudeux, Raphaël Toueg, Michaël Duruisseaux, Jean-Louis Palgen, Perrine Masson, Adèle L'Hostis, Nicoletta Ceres, Claudio Monteiro. Comparison of the effect of two EGFR-TKI in patients with EGFR-mutant lung adenocarcinoma using in silico clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 856.