The Swiss Medicine & Pharmaceuticals,

Applied Ai & ML Propostion in Blood Platelet Analysis & Stemcell Reseach. at University Of Cambridge : 100000 Genomes Project: Stem Cell & Heredity Blood Disease | See Research @ Oxford

    Non Prejudicial Disclosure, Intellectual Property: Doctoral Proposition To,
    Professor Willem H. Ouwehand FMedSci
    Blood transfusion Genomics Consortium
    University Of Cambridge
    BGC Project

    Relevance:Stem Cell Research, Heredity/Blood disorder
    Sept 24, 2021
    The Hague, Netherlands. European Union,EUC

    Click To see Case Study

    In Collaboration With NHS Blood and Transplant (H&I laboratory, NHSBT Colindale, London, UK), the New York Blood Center and Sanquin (Amsterdam, the NL)

    Our Proposal of application of Model driven system of systems’ application with Ai and Support Vector Machine technologies for the following reasons in present research analysis at its present stage, because : this it will assist to deliver the Clinical Study in 2022, assist in relevant cases more optimized, via risk free, transfusion and transplantation

    Secondly, Our specific interest, in Application of Ai and ML approaches in public health and primary care sectors because it brings in a methodological solution with scientific approaches to provide a way one step ahead to solve greater need this sector. With application of Ai and ML from historical and clinical trails data, test cases and their medical methodological cure for each disease, a faster prediction and their recovery timeframe can be attained and rendered to patients. This will enhance the heath care systems overall for governments for both advanced and developing world.

    This includes in specific public healthcare’s Patient healthcare informatics’ improvement thru use of clinical trails data and test cases for various blood borne virus , bacterial strains, cancerous infection, and nephrological data analyzed from end state diabetes patients after blood transfusion and before to analyze kidney heath and functionality prediction, before and after diabetes Type 1 and Type2 diagnosis in CKD, for patterns determination and towards recovery to estimate prediction or life expectancy, in preventative medicine.


    The enhancement of healthcare and primary medicine can be further advanced to mobilize primary care physicians to assist even remotely, to remote distances to these patients and their hopeless families with the advancement of Ai assisted Tele medicine and Diagnostics to reach every corner of under development and developing frontier with new online recuperation techniques relayed instantly, followed up frequently, and with interactive physicians, pharmacy, blood services and organ banks, integrated delivery systems within expedited hours to remote distances.



    Application of ML, Ai Resaerch to NIHR BioResource, University Of Cambridge, UK :

    First of All,

    This will add value to NIHR BioResource whole genome sequencing project, and further pilot studies for rare diseases for the 100000 Genomes Project. The technique shall assist in research on inherited bleeding, thrombotic, platelet disorders and will assist as complements in the associations between common sequence variants and the blood cell parameters measured by the complete blood count, with a focus on platelets. The technique will augment to unravel the genetic architecture of blood cell formation and how this relates to the pathophysiology of common and rare diseases in a more granular stages.

    It will add to core value in blood transfusion and type matching for internal organ transplantation including diabetes type 1, 2 end states, creating collaboration between blood services and organ donor clinics to build fast recommendation systems to assist in technology to separate blood plasma from blood cells in blood transfusion technologies. to classify donors and patients only for DNA variants which are important for selecting the most suitably matched units of blood and platelets for patients requiring regular transfusions.

    It will assist to optimize and perform concordance analysis at both genotype and antigen level, to enhance analysis to fine tune and improve the array design ahead of the Clinical Study in 2022. In pre clinical stage it will assist to evaluate the instrumental data, that is, arrays GENETITAN-MC instruments of three of the Consortium’s member organizations, being NHS Blood and Transplant (H&I laboratory, NHSBT Colindale, London, UK), the New York Blood Center and Sanquin (Amsterdam, the NL) to collaborate with type data classification.

    The optimization with Ai, will assist in large-scale population genome wide association studies (GWAS), from several blood services that are included in GWAS efforts, for the unravelling of the genetic architecture of common diseases and medically relevant traits as per (Vuckovic et al., Cell, 2020.). It will enhance the designing of the accredited two studies of the next versions of the UKBB array (UKBB v2.2) and assist in a new array tailored to the needs of blood services.

    It can assist in evaluation of UK Biobank (UKBB) array (Astle et al., Cell, 2016) in decision making so it could be rendered suitable for the typing of Human Erythroid Antigens [HEA], Human Platelet Antigens (HPA) and Human Leukocyte Antigens (HLA). With samples and antigen typing/classification data from nearly 8,000 blood donors it can further the classification task of all clinically relevant HEA and HPA antigens, by accurate classification, with the UKBBv2 research array.

    It will help in further use of UK Biobank (UKBB) array (Astle et al., Cell, 2016) which could be rendered suitable for the typing of Human Erythroid Antigens [HEA], Human Platelet Antigens (HPA) and Human Leukocyte Antigens (HLA) and assist in necessities required to implement donor and patient genotyping at global scale. HLA class I and class II types, a 2-field resolution, also can be optimized while being inferred from the genotyping results by imputation at high accuracy (Gleadall et al., Blood Advances, 2020).

    Along with, it will help clinical study in areas such as: international partnership between blood services, research institutions and industry leaders in data exchange to improve the safety and efficiency of blood and platelet transfusion by introducing cutting- edge genomics technology into routine clinical practice, at Pre-Clinical Study II and Post / Clinical Study.