Analytics, data automation, and research services company Seven Bridges, has launched ARIA™, a cloud-based platform that includes bioinformatic tools to empower researchers to query and store vast amounts of phenotype and genotype data at the 1M+ participant scale. The company says that the platform, which combines genetics and health outcomes data, will enable faster discovery of new drug targets, identify target populations for precision drugs, develop biomarkers that can be used in a clinical setting for wellness and disease prevention, and allow for in silico modeling of the impact of deactivating a gene.
“Seven Bridges scientists and bioinformaticians have worked closely with researchers to help them interrogate massive datasets to better understand the links between genomic data and health outcomes,” said Brandi Davis-Dusenbery, Ph.D., CSO of Seven Bridges, in a press release. “We’re designing ARIA to make it faster and easier for researchers to ask important questions instead of losing time performing organization and orchestration of petabyte-scale datasets.”
Around the world there are a growing number of both public and private research efforts underway that are looking to collect and leverage genomic and phenotypic data from tens and even hundreds of thousands of people for research purposes. Genomics England and its 100,000 Genomes Project is perhaps the most recognized effort, but other similar efforts are underway in as many as a dozen other countries, at pharmaceutical companies like AstraZeneca, and at integrated health networks such as Geisinger in the U.S. According to Seven Bridges, ARIA addresses what the company says is a lack of tools available in the market that allow easy interoperability of disparate data at this scale.
ARIA comprises of three core components that Seven Bridges says will help speed new discoveries in a scalable and customizable environment. The three major components of the platform include:
- Phenotype information stored in a flexible and dynamic manner, to enable exploration and selection of cohorts based on complex, compound variables, including a suite of ETL processes for data ingestion and semi-automated data harmonization across different studies
- A variant data warehouse with a standard schema for querying whole-genome data at scale, while schema standardization provides a basis for interoperability of genomic data housed in diverse geographical regions or between multiple entities. For security, ARIA provides individual-level permissions to ensure strict data access compliance
- A framework for interpreting and integrating genetic variation in the context of hundreds of annotation sources, including the possibility to incorporate custom annotations and biological knowledge to refine hypotheses.
“ARIA enables our research partners to better understand the interplay between genomics and health outcomes and showcases our continued commitment to providing researchers with transformative applications in order to reduce the time, cost, and risk associated with bringing new products to market,” commented Bill Moss, CEO, Seven Bridges. “Looking forward, the capabilities of ARIA set the stage for an impactful application of AI/Machine Learning to further accelerate breakthroughs and ultimately improve health outcomes for patients all over the world.”