Millions of people with chronic inflammatory diseases like rheumatoid arthritis and lupus are still taking drugs that stop working or never work for them at all. These immune-mediated inflammatory diseases (IMIDs) share common biological roots, yet most research collections have focused on just one disease at a time, making it impossible to compare molecular patterns across conditions. This consortium will merge dozens of UK biobanks and clinical datasets into a single searchable resource, linking patient medical records with molecular data from blood and damaged tissues. If successful, the platform will let researchers identify biomarkers that predict which drug works for which patient, allowing doctors to prescribe the right biologic at the right dose from the start. For rarer IMIDs where evidence is scarce, the pooled data could reveal treatment pathways that currently do not exist. The project does not aim to discover a new drug; it builds the infrastructure to make existing and future drugs far more effective, reducing trial-and-error prescribing and saving the NHS money on expensive treatments that fail.
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Immune-mediated inflammatory diseases (IMIDs) are common medical conditions that cause substantial pain, distress, loss of function and early death. They are clinically diverse e.g. by variously targeting the skin, joints, or kidneys, but share some common genetic features, environmental triggers and inflammatory pathologic mechanisms. The IMIDs include rheumatoid arthritis (RA), psoriasis, systemic lupus erythematosus (SLE), Sjogren's syndrome, autoimmune hepatitis and primary biliary cirrhosis. Since the 1990s, biologic drugs and improved treatment strategies have revolutionised the treatment of a significant proportion of people with some IMIDs. However some IMIDs have not really progressed and even in those in which advances are notable, many patients do not yet respond to treatment or lose their responses over time - this in life long incurable diseases. Therefore, there remains great unmet clinical need in the IMID field. One exciting approach to improving outcomes is to apply the principles of precision medicine whereby patients will receive the 'right drug at the right time at the right dose' with minimal chance of having significant toxicity. Bringing precision medicine to IMIDs will require large datasets that integrate clinical information together with complex molecular datasets that can now be generated from the blood and damaged tissues that occur in IMIDs. In theory, by putting this information together we can create a 'molecular map' of a patient that allows very precise treatment decisions to be made that will bring better outcomes at reduced risk. Thus far however most IMID collections of such data have been specified for only one disease leading to a rather narrow approach to the broader inflammation medicine field. This proposal will revolutionise this scenario by bringing together many UK biobank and clinical cohort datasets into one single searchable and analysable entity, lead and coordinated by a consortium called IMIDBio-UK. IMIDBio-UK will generate a virtual information superhighway that will allow unprecedented access to information about IMIDs across the UK. The vision of the IMID-Bio-UK consortium is to harness the power of a rich reserve of biosamples, deeply phenotyped clinical cohorts, and high quality multi-omic data formed from a group of highly successful national stratified medicine programmes. These resources will be made available to researchers to study IMID biology and predict drug response, using molecular markers (biomarkers) to define common and unique mechanisms (endotypes) of disease progression and drug action. This will enable wider, safer use of biologics and new medicines across the IMID spectrum. By bringing together IMID samples and comparing data and clinical practice, we will optimise clinical pathways for common IMIDs, and provide much needed insight into biologic use in rarer or poorly characterised IMIDs, ultimately delivering patient benefit and health care savings.
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