Accelerating precision medicine research

There are more than 60,000 individuals with a rare disorder in our network. We partner with dozens of patient organisations working to raise awareness and support research in rare disease. There are more than 7,000 rare diseases, and with <400 available treatments we are committed to accelerating research in this area.

There are more than 40,000 individuals affected by depression, anxiety, bipolar disorder, and other mental health conditions in our network. Treatments for these conditions have many side effects, and there is a profound gap between treatment promise and symptom relief for most people affected.

Genetics has been found to influence risk of mental health conditions, and treatment response. Research that we support in this area offers hope for making current treatments more personalised and effective.

There are more than 80,000 individuals affected by autoimmune conditions like psoriasis, eczema, rheumatoid arthritis, and systemic lupus erythematosus in our network.

The prevalence of autoimmune conditions has been increasing in the past decades, and current treatments do not work well for the majority of patients. Genetics has an important role to play in identifying individuals at higher risk of developing autoimmune conditions and in making treatment strategies more personalised.

There are more than 10,000 individuals affected by hereditary cancers such as breast cancer, prostate cancer, and colorectal cancer in our network. Advances in genetic data analysis, such as polygenic risk scores, show great promise for predicting hereditary cancer risk.

We are excited to work with researchers to provide clinical and genetic data to help them improve these algorithms, and validate their effectiveness before deployment into clinical care.

There are more than 30,000 individuals affected by cardio-metabolic conditions such as Type 2 Diabetes, Coronary Artery Disease, and Stroke in our network. Advances in early prediction of cardiovascular disease risk using polygenic risk scores and integrating genomic data with other health information are likely to help save lives, and reduce costs in the healthcare system.

We are working with researchers to improve these algorithms and make sure that prediction is effective regardless of ethnicity by working with partners all over the world to analyse diverse data-sets.