High-throughput behavioural platform to advance neurodegenerative disease drug discovery
University of Western Ontario
Development of new drugs for Alzheimer’s disease depends on the use of animal models to test how well these drugs work before they are used in humans. Ideally new drugs should be able to improve memory loss as well as attention deficits, key brain problems, in individuals with Alzheimer’s disease. Unfortunately, testing memory loss in animal models is difficult, because traditional tests used in mice (the choice to model Alzheimer’s) are difficult to implement and can provide variable results.
We are adapting new behavioral tests using touchscreens to determine memory and attention loss in mice that are based on tests used to measure these brain dysfunctions in Alzheimer’s disease. These novel tests are fully automated, decreasing variability of results, and can be applied simultaneously to a large number of animals. We envision the use of these automated tests to help to decide if new drugs being developed to treat Alzheimer’s disease will be able to improve memory loss. We will create the standards to put this novel technology in the service of pharmaceutical industries and academic laboratories developing new drugs to treat Alzheimer’s disease.
Relevance to the acceleration of therapeutics for neurodegenerative diseases of aging
Our proposal will help to determine how effective new treatments will be to improve memory and attention loss in mouse models of Alzheimer’s disease. We hope that this novel approach will allow us to test new drugs faster and with much more confidence than it has been possible until now.
We expect to develop the means to predict which drugs will be effective to treat Alzheimer’s disease. This will provide a technological advance for Canadian pharmaceutical and academic laboratories, as well as international partners, to test their drug candidates prior to clinical trials. Our proposal will lead to faster and more predictable development of drugs for Alzheimer’s disease.