IG16210 - MINDDS-connect: an innovative data and resource sharing platform for real time analysis of patient meta-cohorts for the neurodevelopmental and psychiatric disorders

A significant roadblock for mental health research and innovation is the need to balance sharing of patient data and biological samples with the fundamental rights of the individual to privacy and security of their personal data. There are strong scientific, medical innovation, financial and even ethical benefits from maximising the usage of data and resources by collecting multisite, patient data into meta-cohorts. Analysis of the resulting meta-cohorts will drive improved therapeutic strategies, identification of targets for drug development, inform health policies and will be foundational for a new era of Precision Medicine. However, the rights of the individual must remain unassailable, and data protection is a major economic and security issue at the European level. This issue is most acute for the study of patients who carry high risk genetic variants for the neurodevelopmental disorders (NDD); these include intellectual disability (ID), autism spectrum disorders (ASD) and schizophrenia. Together they constitute a significant contributor to the population mental health burden. Importantly, the strong correlation between specific gene loci and psychiatric risk in these patients creates the opportunity to establish the mechanism(s) underlying the risk of transition from health to illness. The problem is that these individuals are rare in the overall patient population, necessitating a pooling of data and samples for meta-analysis. MINDDS-connect will solve this by enhancing data discoverability and analysis across multiple centres without the need for transfer of patient data or samples. Once demonstrated this innovative solution can be applied to the broader patient population, enabling the formation of virtual meta-cohorts. MINDDS-connect is a novel, web-based, federated data platform, where all data is securely stored on local servers, thus protecting patient privacy, but will allow analysis of anonymised data for registered platform users. Anonymity and security are ensured by data aggregation protocols; the blockchain principles used to protect highly sensitive data, such as the cryptocurrency Bitcoin. The platform consists of local, secure sample catalogues that will expand with ongoing patient recruitment, but are accessible for investigation via a cloud-based informatics toolkit for data meta-analysis. This federated architecture creates a secure platform for real time analysis of anonymised patient genomic and phenotypic data across geographically dispersed sites without the need to transfer individual patient data or store it centrally. The platform has been designed within the MINDDS network and a prototype platform has been created. This COST Innovators Grant (CIG) aims to demonstrate platform implementation across multiple European medical centres. In parallel, it will review all regulatory requirements, instigate a dissemination plan, and create a business plan to ensure sustainability, thus preparing the platform for a public launch. The major outcome of the CIG will be an innovative data platform to support clinical research and industrial innovation by delivering a step change in our capability for meta-analysis of patient data. It will be a major analytical tool with which to implement Open Science policy for data sharing in metal health data, facilitating further innovation in clinical knowledge and practise, improved therapeutics and drugs and support development of the Precision Medicine sector.