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JUL

18. Jul 2019

TissueGnostics joins the European conversation about re-use of health data


HELICAL: HEalth data LInkage for ClinicAL benefit is a Marie Sklodowska-Curie innovative training network comprising 17 academic and 9 non-academic/industry partners for early stage researchers in the field of Healthcare Data Linkage in the machine learning and GDPR era. HELICAL exploits recent advances in data science to link research datasets with longitudinal healthcare records, based on the robust ethical foundation required for linkage studies using near-patient data, to address key experimental questions.

Trinity College Dublin and Tallaght University Hospital researchers have coordinated a successful H2020 bid with a value of €4.05 million for a collaborative project involving 23 partners across Europe, linking healthcare data in autoimmune disease.

HELICAL: HEalth data LInkage for ClinicAL benefit is a Marie Sklodowska-Curie innovative training network comprising 17 academic and 9 non-academic/industry partners for early stage researchers in the field of Healthcare Data Linkage in the machine learning and GDPR era. HELICAL exploits recent advances in data science to link research datasets with longitudinal healthcare records, based on the robust ethical foundation required for linkage studies using near-patient data, to address key experimental questions.

European researchers and patients have made leading contributions to the large genomic, transcriptomic and clinical datasets from patients with chronic autoimmune diseases. Advances in information science provide unprecedented opportunities for using these datasets to elucidate the complex biology of these disorders, its influence by environmental triggers, and to personalise their management. Exploitation of these opportunities is currently limited by a shortage of researchers with the required informatics skills and knowledge of requisite data protection principles. HELICAL addresses this unmet need by developing a trans-sectoral and interdisciplinary programme with training in analysis of large datasets, using autoimmune vasculitis as a paradigm.

The HELICAL training programme focuses on three complementary areas: application of informatics to large datasets to gain new biological insights; translation of biological into practical clinical outputs and identification of the novel ethical constraints imposed on such studies and development of strategies to manage them.

In terms of patient care, HELICAL researchers will foster a precision medicine approach in vasculitis by developing tools that can identify and predict disease flare and inform the clinician about opportunities to increase or discontinue immunosuppressive medication. The approach will also identify therapeutic strategies that target relevant components of the immune system and blood vessel wall, leaving intact the ability to fight infection and malignancy. Additionally the researchers aim to develop technology that will deliver self-management tools via the patient’s smartphone.

Mark Little HELICAL Professor of Nephrology and Consultant Nephrologist, Dr Mark Little said: “For Trinity, the successful bid links the School of Medicine, the School of Computer Science and Statistics, the ADAPT Centre and the College at the heart of a European conversation about the re-use of health data and artificial intelligence at the dawn of the GDPR era.”

“By combining the innovation strength of the leading European vasculitis and machine learning researchers, in close collaboration with affected patients, we aim to learn about how the immune system interacts with our environment at an exposome, genetic and protein level. Irish funder support through Enterprise Ireland, Health Research Board, the Irish Nephrology Society and Meath Foundation provided the basis for this application, which was ranked joint first of 1714 applications.”

Read more at www.helical-itn.eu

EU logo HELICAL 150x150This project has received funding from the European Union’s Horizon 2020
research and innovation programme under the
Marie Sklodowska-Curie grant agreement No 813545

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