The precision medicine initiative coupled with advances in genomic research and diagnostics is leading to vast increases in the volume of genomic data being created, with some estimates stating it will outstrip the storage requirements of YouTube by 2025. Ensuring all this data can be cost-effectively managed, and that experts from the biomedical, informatics and medical disciplines can easily collaborate on analysis, and interpretation of results is critical for genomic medicine to realise its potential, both in research, and at the point-of-care. This proposal will develop an easy-to-use, web-based platform to manage and visualize the vast amounts of genomic data already available and projected to be generated. This platform will access data across distributed file systems, and, via a powerful API, connect to customers cloud, or local hardware pipelines and analysis tools. As companies transfer data to the cloud, or use the cloud as an overflow to their internal storage, this data hub will provide uninterrupted data access. Data will be managed in a highly visual environment, providing visual analytics of all available data, and the ability to generate data subsets using search functionality provided by interactive charts and standard text search. Automated data and consistency checks will be performed, and integrated apps built on the IOBIO platform will enable intuitive data analysis, with all results stored, and shareable from within this data hub, promoting close collaboration on projects. Rather than being reduced to static reports, or Excel style spreadsheets, results are stored in the data hub and within these apps. This means that the link between results are supporting data are never severed, so analyses can be repeated, reviewed, or updated based on modified assumptions or data with ease. The objective of this proposal is to develop a commercially viable product to make management of, collaboration on, and understanding of genomic data a reality for medical professionals as well as informatics experts, diagnosticians, and biomedical researchers. Reducing the costs associated with genomic analysis will ensure it can be scaled to support individual focused medicine, and be attractive to a wide customer base. The product is designed for growth, with the addition of analysis modules focused on Mendelian disease genetics and oncology, among others, planned for the future.
This project will democratize genomic analysis by providing intuitive data management, organization, data analytics, and integrated visually driven analysis in a single application, that can be used by experts across the bioinformatics research and the healthcare disciplines. My simplifying organization and improving collaboration, this project will reduce the costs associated with genomic analysis, while simultaneously improving research results and diagnostic outcomes.
