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Semi‐mechanistic modelling platform to assess cardiac contractility and haemodynamics in preclinical cardiovascular safety profiling of new molecular entities
Author(s) -
Venkatasubramanian Raja,
Collins Teresa A.,
Lesko Lawrence J.,
Mettetal Jerome T.,
Trame Mirjam N.
Publication year - 2020
Publication title -
british journal of pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.432
H-Index - 211
eISSN - 1476-5381
pISSN - 0007-1188
DOI - 10.1111/bph.15079
Subject(s) - preload , medicine , contractility , safety pharmacology , cardiology , hemodynamics , heart rate , mean arterial pressure , population , blood pressure , pharmacology , drug , environmental health
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 max ), heart rate (HR) and mean arterial pressure (MAP) in preclinical studies. Experimental Approach Data from dPdt max , 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 G –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 max . Key Results The model was able to describe drug‐induced changes in dPdt max , HR and MAP for all drugs included in the developed framework adequately, by incorporating appropriate drug effects on dPdt max , HR and/or total peripheral resistance. Consistent with the Starling's law, incorporation of LVEDP as a covariate on dPdt max 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.