FEB 09, 2017 9:00 AM PST

Improved decision making in the drug discovery process using an innovative approach to modelling chronic liver disease

Speaker

Abstract

DATE: February 9, 2017
TIME: 9:00am PT, 12:00pm ET

Traditional models of liver fibrosis in rodents involve many weeks of induction, with frequent injections of a pro-fibrotic agent. The most commonly used end-point in these studies is immuno-histochemical analysis of markers of fibrosis in the liver. This whole process is time-consuming, very labor-intensive in terms of animal handling, processing of the tissues and produces only a semi-quantitative measure of fibrosis. In addition, if pharmacological agents are to be explored, this means more ‘hands-on’ work for the experimentalist due to the likelihood of the need for daily dosing and adds substantially to the cost of the study because of the amounts of compound required. We have modelled the inflammatory component which drives liver fibrosis, by using the concanavalin A (conA) challenge to evoke an acute liver inflammation and the Vium ‘Digital Vivarium’ as a way of monitoring mouse behavior in response to the challenge. Acute liver inflammation evokes measurable changes in mouse behavior over the course of 24hrs and we believe these behavioral measures will be useful in testing the efficacy of pharmacological agents which suppress the inflammation.  By focusing on the inflammatory drivers of the pathology we dramatically reduce the duration of the studies, obtain a quantitative measure of the effect of the conA whilst minimizing handler intervention and reduce compound demand. Moreover, we believe the value of efficient in vivo testing of hypotheses enables us to embrace ‘systems biology’ in a way that is entirely compatible with aspects of the ‘3Rs’. Using a behavioral assessment of inflammation enables us to make rapid decisions on mechanisms and targets of interest. This reduces costs and time but maybe more importantly, promotes improved iterative decision-making regarding targets and compounds.


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FEB 09, 2017 9:00 AM PST

Improved decision making in the drug discovery process using an innovative approach to modelling chronic liver disease



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