To understand disease at a deeper than ever biological level, to enable us to better predict the onset and progression of ill-health and tailor medicines for sub-types of disease (instead of a one-size-fits-all approach), as well as predict patients’ reaction to medicines.
Traditionally, diseases are defined by symptoms, which normally relate to one organ or area of your body, e.g. heart disease, asthma. However different diseases can have similar symptoms (clinically similar) but completely different causes (differing aetiology), and vice versa. Partly as a result of this, most medicines are effective in only about a third of patients who take them. One challenge is to find ways to treat disease based on underlying cause rather than symptoms, enabling us to link the right medicine, to the right person, at the right time, to give us the best chance of curing people or reducing their symptoms.
We plan to use data resulting from the formidable array of technologies available today that can describe the many facets of human disease in incredible detail – and then link these very different types of health measurements together with health outcomes. We will reveal insights into biology and disease by integrating this kind of information at scale, which includes measures of the genes switched on in a person, levels of proteins in blood samples, digital scans (e.g. x-rays, MRI, PET) and even data that describe how your genes interact with the environment throughout your life. These layers of biodata will be linked to health outcomes using electronic health records to develop better, more targeted treatment for disease.
Teamwork is key – we will share the knowledge we generate through this research with existing major national initiatives which are contemplating or conducting related work. This may include UK Biobank, the 100,000 Genomes Project, NIHR BioResource, Deciphering Development Disorders and the nascent Genomic Medicine Service.
We will mobilise a shift in health service delivery, from disease classification based on pattern of symptoms, to one based on molecular underpinnings. Effectiveness of medicines will improve so that people will get better quicker. Diverse types of patients’ medical data will be used routinely and appropriately linked together to teach us how to deliver the most effective treatments, to keep our population healthy and treat them more effectively when disease strikes.