Rat cardiovascular telemetry: Marginal distribution applied to positive control drugs

• Published in: Journal of pharmacological and toxicological methods Vol. 81; pp. 120 - 127
• Main Authors: Accardi, M.V., Troncy, E., Abtout, S., Ascah, A., Maghezzi, S., Authier, S.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-09-2016
• Subjects: Animals; Body Temperature - drug effects; Cardiovascular Physiological Phenomena - drug effects; Cloud analysis; Contractility; Data Interpretation, Statistical; ECG; Electrocardiography - drug effects; Electrodes, Implanted; Heart Rate - drug effects; Left ventricular; Long QT Syndrome - chemically induced; Long QT Syndrome - physiopathology; Male; Myocardial Contraction - drug effects; Rat; Rats; Rats, Sprague-Dawley; Safety; Telemetry; Telemetry - methods; Ventricular Function, Left - drug effects; PR; QT; Rat; Contractility; Left ventricular; ECG; Cloud analysis; Telemetry
• ISSN: 1056-8719; 1873-488X
• DOI: 10.1016/j.vascn.2016.03.005

Cardiovascular effects are considered frequent during drug safety testing. This investigation aimed to characterize the pharmacological response of the conscious telemetered rat in vivo model to known cardiovascular active agents. These effects were analyzed using statistical analysis and cloud representation with marginal distribution curves for the contractility index and heart rate as to assess the effect relationship between cardiac variables. Arterial blood pressure, left ventricular pressure, electrocardiogram and body temperature were monitored. The application of data cloud with marginal distribution curves to heart rate and contractility index provided an interesting tactic during the interpretation of drug-induced changes particularly during selective time resolution (i.e. marginal distribution curves restricted to Tmax). Taken together, the present data suggests that marginal distribution curves can be a valuable interpretation strategy when using the rat cardiovascular telemetry model to detect drug-induced cardiovascular effects. Marginal distribution curves could also be considered during the interpretation of other inter-dependent parameters in safety pharmacology studies.