IssueJune 22Opinion

Role of AI in Transfusion Medicine

AI will play a big role in transfusion medicine in managing the inventory, predicting the variations in demand and predicting the blood requirements for different procedures. An insight by Dr Anand Deshpande, Consultant  Transfusion Medicine & Hematology, PD Hinduja National Hospital & MRC Mahim, Mumbai

Transfusion Medicine is one of the branches in medicine which is involved in both the clinical management of the
patients as well as laboratory aspects. It has come a long way from being just a blood bank wherein only whole blood was collected and issued, to a blood centre/transfusion medicine department with all the advanced modern
technologies. On the laboratory front, transfusion medicine has developed in various directions. Initially, only whole blood was issued to the patients, now most of the blood centres are preparing 100 per cent blood components such as Packed Red Blood Cells (PRBC), Random Donor Platelets (RDPs), Fresh Frozen Plasma (FFP), Cryoprecipitate (Cryo) & issuing to different patients as per the clinical requirements. This has led to
the rational use of blood components optimising the inventory and minimising the losses.


Using the Apheresis technology ( use of cell separator ), the Blood Centres can collect a single product such as platelet, plasma, granulocytes or even Peripheral Blood Stem Cells (PBSC ). Newer modalities such as Immunoadsorption, Extra Corporeal Photopheresis are used to treat different diseases.

To avoid Adverse Transfusion Reactions (ATRs), blood centres have started using Inline filter bags to remove unwanted White Blood Cells (WBCs) which are responsible for the majority of ATRs. Irradiation of blood is carried out by blood centres in transplant cases. In India, it is mandatory to test all the blood units for HIV, HBV and HCV by ELISA / CMIA method. Other mandatory tests are Venereal disease (VDRL) testing and malarial parasite (MP). A major advancement in this area is the Nucleic acid Amplification Technique (NAT). It helps to reduce the ‘window period’ drastically and makes the blood safer for the recipient. Hopefully, in near future, this technology will be adopted by all the Blood centres in India.

Pathogen reduction technologies are already being used in many countries. As far as the red cell testing is concerned it is gradually moving from serum-based assay to molecular techniques-based assay. Initially, blood groups were done routinely using slide methods, now the blood centres are using automation with
column agglutination/ bead/solid-phase assays, helping in reducing the errors and shortening the Turn around Times (TATs). Cross-matching i.e. checking the compatibility of the recipient and donor blood has also moved from the  slide method to computer crossmatch / electronic crossmatch. Many centres are giving  phenotype/antigen-matched blood to minimise the formation of antibodies in recipients. On the clinical side, transfusion medicine consultants are involved not only in routine blood transfusions but also in the proper use of different blood components in correct doses as per the clinical requirements. They are also involved in managing the patients (adult and paediatric group) with bleeding disorders, platelet disorders and coagulation disorders. They play a major role in peripheral blood stem cell harvest (PBSC) as well as Bone Marrow Transplants (BMT). Different therapeutic apheresis procedures such as Therapeutic Plasma Exchange, Therapeutic Red Cell Exchange are carried out by them in various clinical disorders.

Computerisation and AI
From the donation of blood to transfusion to a recipient donor arm to the patient arm is a long chain and
involves many persons. The probability of errors increases manifold as a large number of people are involved in  various activities such as the collection of blood, preparing the blood components, testing the blood units, cross-matching the blood, issuing the blood units and ultimately transfusion to the patient. This has led to the use of software in all the blood bank operations to reduce/ minimise errors. In the coming years, AI will play a big role in transfusion medicine in managing the inventory, predicting the variations in demand, predicting the blood requirements for different procedures and even better management of donors. However, AI requires Big data for better predictions and the Blood centres will have to use software for all their operations so that the data production and acquisition will be uniform and standard.

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