Pierre-Antoine GOURRAUDCentre de recherche en transplantation et immunologie (CRTI) - Inserm / CHU de Nantes
Mes recherches
Shortly after receiving the ATIP-Avenir Award, I became a university professor and hospital practitioner (Medical School, Nantes University, France) in 2015, while being an associate professor at the Department of Neurology of the University of California at San Francisco (UCSF), USA.
In Nantes, in addition to my teaching activity, I led a fast-growing Inserm research team that involved over 20 members two years after its creation and already attracted two international recruits. Over the past ten years, I have established fruitful research collaborations with a large network of academic and industrial investigators from all over the world and developed a unique set of skills which puts my group in a unique position to oversee research projects at the crossroads of computational modelling, bioinformatics and epidemiology. I am the co-author of 130 peer-reviewed publications including 42 as lead author (>6200 citations, Index H: 42).
In addition, I am the coordinator of the “Data Clinic”, which brings together the Clinical Epidemiology group of the CIC INSERM 1413 and experts of the public health and epidemiology Unit (PHU11 UF7215). The “Data Clinic” promotes methodological and population-level analyses of integrated biomedical data. Governance and technical aspects of this new type of hospital organization has been heavily influenced by my research in Immunogenomics. The unit provides support for hospital investigators of the Nantes University Hospitals community by assisting clinical research with data extraction and computational analyses. Since July 2018, by approval of the French Data Protection Authority (CNIL), the “Data Clinic” has been central to the internal governance of the biomedical data warehouse. The database currently enables the deployment of complex queries concerning: 2.6 million patients, 9 million encounters, 24 million documents and 130 million structured data.
Mon projet ATIP-Avenir
A new paradigm for data usage and algorithms in precision medicine for transplantations and multiple sclerosis.
While precision medicine promises to transform the delivery of care to patients, such promise faces a critical challenge: the conceptual basis of existing algorithms is lacking. The emergence of a new generation of decisional algorithms leveraging on-demand computational power and online access to multiple sources of massive reference data represents a formidable opportunity to make personalised patient care a clinical reality.
This proposal will develop the basis of a new generation of algorithms that will adopt, via computational design, a true patient-centric approach: they will use the patient of interest (POI) as the starting point of all computations and queries of reference data. We claim that such paradigm shift has the potential to supplement averaged rules and fixed protocols in clinical practice.
At the crossroads of public health analytics, computational modelling of decisional process in medicine, epidemiology and bioinformatics, it combines and integrates the major types of reference biomedical data (Randomised Control Trial, Epidemiological Cohort and Registries, Electronic Medical Records), turning these large amounts of data into actionable information for clinicians. By targeting multiple medical conditions (multiple sclerosis, transplantations) that differ by aetiology and therapeutic options, but share a central costly chronic dimension, the project will provide paradigmatic tools that will be more widely applicable to healthcare.
We use the three dimensions of medical assessment for decision-support: comparison of patient profiles, evaluation of the relevance of (additional) information (e.g., labs, expertise, imaging, biomarkers), and prediction of both outcome and outcome uncertainty under various therapeutic scenarios.s.