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Supat Thongjuea is an Oxford-BMS Research Fellow in Radcliffe Department of Medicine. Here he discusses his project and benefits he has drawn from his experience.

Supat Thongjuea

What is your research background?

My research background is in computational biology. I apply computational techniques for the analyses of large-scale sequencing data generated by single-cell multi-omics approaches. My main focus is to study normal and malignant hematopoiesis. The aim is to combine single-cell methods and computational analyses to identify gene-targets that may be translated into novel diagnostic and therapeutic interventions for poor prognosis and drug resistance in blood cancers, particularly in myeloid leukemia.

What are you researching now?

My current research focuses on applying multi-omics single-cell approaches for studying Acute Myeloid Leukemia (AML) with TP53 mutations. In AML, ~5-10% of patients carry TP53 mutations. This subset of patients has short survival with poor chemotherapy response, whereas the long-term survival of TP53 mutant patients from the stem cells allogeneic transplantation is rare. Therefore, there is a critical need to identify novel therapeutic targets for this subset of patients.

What has your experience with this Fellowship been like?

The Oxford-BMS fellowship has provided me with the opportunity to develop skills to interact with a leading global biopharmaceutical company. Such an interaction is uniquely made possible through this fellowship programme. It is a significant experience for me to work and interact with BMS scientists, allowing me to gain exposure and enter the field of commercial drug discovery.

What are your aspirations for the future of this research?

I would hope this research will bring out novel therapeutic targets for AML patients. The identified targets from my research will be further validated and tested in the drug discovery pipeline. I would hope to see that we can practically translate the data interrogation from single-cell genomics approaches for a clinical application that will help patients have a better quality of life.