Semi-mechanistic modelling platform to assess cardiac contractility and haemodynamics in preclinical cardiovascular safety profiling of new molecular entities.

Background And Purpose: Cardiovascular safety is one of the most frequent causes of safety-related attrition both preclinically and clinically. Preclinical cardiovascular safety is routinely assessed using dog telemetry monitoring key cardiovascular functions. The present research was to develop a semi-mechanistic modelling platform to simultaneously assess changes in contractility (dPdt ), heart rate (HR) and mean arterial pressure (MAP) in preclinical studies.

Experimental Approach: Data from dPdt , HR, preload (left ventricular end-diastolic pressure [LVEDP]) and MAP were available from dog telemetry studies after dosing with atenolol (n = 27), salbutamol (n = 5), L-N -nitroarginine methyl ester (L-NAME; n = 4), milrinone (n = 4), verapamil (n = 12), dofetilide (n = 8), flecainide (n = 4) and AZ001 (n = 14). Literature model for rat CV function was used for the structural population pharmacodynamic model development. LVEDP was evaluated as covariate to account for the effect of preload on dPdt .

Key Results: The model was able to describe drug-induced changes in dPdt , HR and MAP for all drugs included in the developed framework adequately, by incorporating appropriate drug effects on dPdt , HR and/or total peripheral resistance. Consistent with the Starling's law, incorporation of LVEDP as a covariate on dPdt to correct for the preload effect was found to be statistically significant.

Conclusions And Implications: The contractility and haemodynamics semi-mechanistic modelling platform accounts for diurnal variation, drug-induced changes and inter-animal variation. It can be used to hypothesize and evaluate pharmacological effects and provide a holistic cardiovascular safety profile for new drugs.