The evaluation of drug-induced changes in cardiac inotropy in dogs: Results from a HESI-sponsored consortium

Abstract

IntroductionDrug-induced effects on the cardiovascular system remain a major cause of drug attrition. While hemodynamic (blood pressure (BP) and heart rate (HR)) and electrophysiological methods have been used in testing drug safety for years, animal models for assessing myocardial contractility are used less frequently and their translation to humans has not been established. The goal of these studies was to determine whether assessment of contractility and hemodynamics, when measured across different laboratories using the same protocol, could consistently detect drug-induced changes in the inotropic state of the heart using drugs known to have clinically relevant positive and negative effects on myocardial contractility. MethodsA 4×4 double Latin square design (n=8) design using Beagle dogs was developed. Drugs were administrated orally. Arterial blood pressure, left ventricular pressure (LVP) and the electrocardiogram were assessed. Each of the six laboratories studied at least 2 drugs (one positive inotrope (pimobendan or amrinone) and one negative inotrope) (itraconazole or atenolol) at 3 doses selected to match clinical exposure data and a vehicle control. Animals were instrumented with an ITS telemetry system, DSI's D70-PCTP system or DSI's Physiotel Digital system. Data acquisition and analysis systems were Ponemah, Notocord or EMKA. ResultsDerived parameters included: diastolic, systolic and mean arterial BP, peak systolic LVP, HR, end-diastolic LVP, and LVdP/dtmax as the primary contractility index. Blood samples were drawn to confirm drug exposures predicted from independent pharmacokinetic studies. Across the laboratories, a consistent change in LVdP/dtmax was captured despite some differences in the absolute values of some of the hemodynamic parameters prior to treatment. DiscussionThese findings indicate that this experimental model, using the chronically instrumented conscious dog, can accurately and consistently detect changes in cardiac contractility, across multiple sites and instrumentation systems, and that data obtained in this model may also translate to clinical outcomes.