Leveraging large-scale genetic and molecular datasets and to identify novel drug targets and repurposing opportunities for cardiovascular disease
Approved Research ID: 80891
Approval date: March 18th 2022
Cardiovascular disease (CVD) is currently the leading cause of death worldwide. In many CVD types, the availability of drug treatments is vital to remove or delay the need for invasive treatments that cause a disproportionate burden on healthcare systems. Cardiovascular drug development has particularly low success rates when compared to other therapeutic areas, contributing to its deprioritisation by pharmaceutical companies. Despite being faster and cheaper, investigations into repurposed drugs are still liable to failure, especially at late-stage testing.
Mendelian randomisation (MR) is a statistical method which takes advantage of the natural variation of DNA in the population to estimate of the effect of an exposure on a disease. MR studies have been used to estimate whether a drug will be successful in clinical trials. We will use this method to test whether several candidate drugs will be effective against different types of cardiovascular disease. We will then employ another genetic statistical method called PheWAS to test whether these candidate drugs would have adverse side effects.
This project will last approximately 36 months and result in several publications.
Estimating candidate drug safety and efficacy, the key criteria for the its approval to the market, would be key to saving time, money and resources. Additionally, our results might identify promising drug pairings for combined therapies. The existence of drugs that halt disease progression or delay the need for surgery would result in a better quality of life for CVD patients and alleviate some pressure and costs to the NHS.