In Silico Safety Pharmacology on Intersubject Variability Population of Models: A Regression Model Approach

Ana Maria Sanchez de la Nava1, Alejandro Liberos2, Ismael Hernández-Romero3, Maria de la Salud Guillem Sánchez4, Felipe Atienza5, Francisco Fernandez-Aviles5, Andreu M. Climent6
1Hospital GU Gregorio Marañón, IiSGM, CIBERCV, Madrid, 2Hospital GU Gregorio Marañón, Cardiology Department. IiSGM. CIBERCV, 3University Rey Juan Carlos, 4Universitat Politècnica de València, 5Hospital GU Gregorio Marañón, IiSGM, CIBERCV, 6Hospital Gregorio Marañón


Introduction: Safety pharmacology aims towards identifying undesirable effect of drugs during its development phase. However, limitations are present in in-vitro and preclinical research because of its low detection efficacy during this process. Aims: To study the effect of drugs at in-silico tissue level and evaluate inducibility in a multivariable scenario by using a regression model. Methods: 127 mathematical models were tested for two different tissue sizes (basal: 15cm2, dilated: 20cm2) during control and isoproterenol. Reentrant activity was induced with a S1S2 protocol. Proarrhythmic and antiarrhythmic effects of the drug on the tissue were studied, including AF maintenance duration (MD). Results of these simulations were compared with the predictions of a new regression model based on Canonical Correlation Analysis (CCA) (i.e. 80% of the models (N=101) were used as training set, whereas the remaining 20% samples were used as test set). Results: Dilated atria resulted in a larger number of models with AF induction (basal: 80 models, dilated: 88 models) and with longer MDs (basal: 394ms, dilated: 681ms). Isoproterenol exhibited an overall proarrhythmic effect, increasing the mean AF MD on both tissue sizes. However, isoproterenol was antiarrhythmic in a part of the database (Fig 1). CCA analysis obtained 96% accuracy on the test set for basal size and 100% on the dilated one, allowing the identification of drug effect without the need of highly time-consuming simulations. Conclusions: A new promising methodology was proposed for fast in-silico safety pharmacology including variability between patients, setting the base for improving the drug development process and precision medicine.