Title: Artificial intelligence systems to improve the safety, efficiency and clinical outcomes of blood transfusion by the precise genetic matching of patients to blood units
Funder: Department of Health and Social Care

Abstract: Each year, 1.4 million units of blood are donated, providing transfusion treatment to over 700,000 NHS patients. Transfusion can be life-saving for patients with cancer or inherited red blood cell disorders or after blood loss caused by trauma or childbirth. The formation of antibodies against red blood cell antigens (sensitisation) is a well recognised complication of blood transfusion, arising from donor antigens mismatched to the patient. Once sensitised, further transfusions of blood must be matched very carefully or the patient's body may destroy the donated blood, leading to severe illness or even death. Sensitisation is especially common in patients with sickle cell disease who are dependent on transfusion. 17% of the sickle cell disease patients requiring transfusion in the UK have developed antibodies.[1] These patients are overwhelmingly of African ancestry and it can be very difficult to identify compatible blood for them under the current system of provision, because some blood types common in Africa are very rare in the NHSBT donor population, which is largely of European ancestry. We have developed an affordable DNA-test that can measure the blood types of all the human blood groups, which we are accrediting for clinical use. This test will allow NHSBT to measure the complete blood types of hundreds of thousands of blood donors and allow patients to be matched precisely to donated blood, whatever the ancestry of the donor. We seek support to prototype the AI algorithms required to implement precision blood matching routinely in the NHS. This includes algorithms to: translate measured genotypes into blood types ( bloodTyper ), identify the best matched units of blood for patient transfusions ( bloodMatcher ), optimise the mix of blood types in NHSBT stock by prioritising donor invitations ( bloodStocker ), link hospital and NHSBT computer systems to allow the automatic matching and ordering of blood ( bloodLinker ).

Lay abstract: Each year, two million donations of blood are given to provide life-saving treatment to over 700,000 patients. Transfusion is essential to save the lives of patients with major bleeding (e.g. trauma), to treat patients whose blood production is damaged (e.g. cancer), and to treat patients who cannot make healthy haemoglobin (e.g. sickle cell disease). Red blood cells have molecules on their surface called antigens, which people inherit in different combinations. Current practice is to match blood for transfusion to the patient s antigens, but this is usually only possible for the antigens of the major blood groups, for which donor blood is currently tested. Antigens of the many minor blood groups are usually not matched as the current tests are too expensive. Hence mismatches between the transfused donated cells and the cells of the patient s frequently occur. This can cause life-threatening reactions in which the transfused cells are rapidly broken down by antibodies formed by the patient.These make it more difficult to find compatible blood for future transfusions; in some cases there may be none. Blood types are determined by approximately 40 genes. Consequently, DNA taken from a blood sample can be tested to determine the blood s type. We have developed a new method for testing the genes which is cheap and can be applied to patient and donor blood samples. This should allow better matching of donor blood. However we first need to be able to convert the letters of the DNA sequence measured by this test into blood types. With collaborators, we have developed a computer programme called BloodTyper to do this, enabling medical professionals to view a result they can interpret. Other processes for provisioning blood for patients, also need to be automated: Picking the blood units. Currently, laboratory scientists pick units from blood stocks for patients. This does not always lead to the best allocation of units to patients and occasionally there is human error. A programme called BloodMatcher has been developed by our collaborators in the Dutch blood service to overcome these problems by automatically allocating units. Stocking the correct blood. Currently, we encourage blood donation from across the population, with some emphasis on the Black, Asian and Minority Ethnic (BAME) community whose rare blood groups are frequently required. This approach doesn t target donors with specific blood types so we don t always have the blood required for patients. Once many donors have been tested genetically, we can ask specific volunteers to donate blood to meet the needs of patients. This automated system will be called bloodStocker. Our objective is to develop an automated system that will provision precisely matched blood to patients, reducing the complications of transfusion, improving efficiency and reducing waste.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: BLOOD