LB-015 - A TRANSLATIONAL COMPUTATIONAL MODEL OF ALLERGEN CHALLENGE TO SUPPORT THE CLINICAL DEVELOPMENT OF AN INTRANASALLY ADMINISTERED BACTERIAL LYSATE IN MILD ASTHMA.

C. León¹, I. Faddeenkov¹, T. Galland¹, L. Lehr², C. Sansone², A. Vaslin Chessex², C. Pasquali², A. Kulesza¹, S. Arsène¹; ¹Novadiscovery, Lyon, France, ²OM Pharma, Meyrin, Switzerland.

Background: Intranasal administration of the immunomodulatory bacterial lysate OM-85 is currently investigated in asthma. The mechanism of action and protective effects have been demonstrated by preclinical experiments. However, critical questions arise with the translation into clinical development. A computational mechanistic translational approach could provide valuable insights.

Methods: We developed an inter-species mechanistic model of allergen challenge in allergic asthma coupled with a PBPK-PD model of intranasal OM-85. The model in mice was calibrated using a collection of published literature on immune dynamics following various allergen challenges and the effect of knock-out strains or depletions. Treatment specific ADME and preclinical efficacy data was used to inform the PBPK model and efficacy-related parameters. We performed the translation to humans through inter-species allometric scaling and adjustment of the type-2 immune response activation to account for locally built-up memory.

Results: The calibrated model reproduces the observed dynamics of 11 key immune variables following an allergen challenge in mice and in humans. Interfacing this with the PBPK-PD model allowed us to reproduce the large panel of preclinical studies. After translation to humans, we computationally studied the response to an allergen challenge in a first-in-human intranasal administration of OM-85 with a range of doses and treatment durations. We obtained insight into the regimen most likely to effectively reduce asthma symptoms following the challenge.

Conclusion: Here, with intranasal administration of OM-85, we show that our model can support clinical development of novel therapeutic options in asthma. The model will be further consolidated with new data from human trials to validate the model's predictions.