Queen Mary University of London has appointed four research fellows to its new Rutherford Academy of Population Genomics and Health Data Science, funded by the Medical Research Council and UK Research and Innovation's Rutherford Fund. Two of the fellows include BCI’s Dr Kit Curtius and Dr Dayem Ullah.
Queen Mary’s new Rutherford Academy will be aligned to its research as a partner of the London substantive site of Health Data Research UK - a major new initiative to transform health through data science. Forty two of these prestigious fellowships were awarded following a rigorous national competition, resulting in four fellowships at Queen Mary out of a total of fourteen awarded to London universities.
The Rutherford Academy will create an enabling interdisciplinary research environment at Queen Mary for outstanding health data science researchers and deliver a programme of seminars and lectures, as well as training and networking opportunities.
Advancing research in cancer, heart disease and population health
The fellows will be working on a range of projects looking at the detection of gastrointestinal cancers, the progression of pancreatic cancer, the effect of geography and environment on population health, and the use of health records in monitoring the progression of heart disease.
BCI’s Prof Claude Chelala from the Rutherford Academy Leadership Team said:
We are delighted to have been awarded this prestigious grant securing four Fellowships at Queen Mary. This impressive success is the result of the fantastic partnership we have formed across the university and has attracted exceptionally talented fellows. I have no doubt our fellows will succeed in advancing health data research at Queen Mary and nationally.
The Rutherford Academy faculty also includes Dr Mike Barnes, Prof Carol Dezateux, Dr Damian Smedley, Prof Panos Deloukas, Prof Norman Fenton, Dr Borbala Mifsud and Prof David van Heel, and involves Queen Mary’s Life Sciences Initiative and the School of Electronic Engineering and Computer Science.
Early diagnosis of gastrointestinal cancers
Dr Curtius’ project aims to connect multiple levels of information, from genomic to population-based data, via mathematical modelling to help with detection and early diagnosis of gastrointestinal cancers. Dr Curtius will be mentored by Professors Trevor Graham and Stephen Duffy.
Dr Curtius said:
With more and more multiscale data being generated, we can utilise mathematics in new and exciting ways to quantify the important patterns and timescales driving cancer evolution during a patient’s lifetime with increasing precision.
My goals are to use mathematical modelling to weave this information together to reveal the significant characteristics of a patient’s disease history underpinning a more general diagnosis, and to ultimately translate this information to be accessible in healthcare decision-making.
Progression of pancreatic cancer
Dr Ullah’s project endeavours to identify more accurate diagnostic and prognostic factors of the disease. The project will aim to integrate genetic data from patients with environmental risk factors and clinical prognostic factors to understand how these factors interact and contribute to the onset and progression of pancreatic cancer. Dr Ullah will be mentored by Professors Claude Chelala and Hemant Kocher.
Dr Ullah said:
The application of MPE has already yielded useful results for lung, colorectal and breast cancer. By developing novel insights on the relationship among environmental factors, molecular profile and disease status, the project will hopefully enrich the existing evidence-based clinical practice for pancreatic cancer.