As a result of recent scientific advances, there is a tremendous amount of biomedical research data and data available from disease classifications, health records, clinical trials and adverse event reports that could be useful for understanding health and disease and for developing and identifying treatments for diseases. Ideally, these data would be mined collectively to provide insights into the relationship between molecular and cellular processes (the targets of rational drug design) and the signs and symptoms of diseases. Currently, these very rich yet different data sources are housed in various locations, often in forms that are not compatible or interoperable with each other. All of these factors limit the ability to get more treatments to more patients more quickly.
To address these problems, NCATS launched the Biomedical Data Translator program, called “Translator” for short. This multiyear, iterative effort will culminate in the development of a comprehensive, relational, N-dimensional Biomedical Data Translator that integrates multiple types of existing data sources, including objective signs and symptoms of disease, drug effects, and intervening types of biological data relevant to understanding pathophysiology.
Watch this video to hear NCATS Director Christopher P. Austin, M.D., explain the purpose and goals of the Biomedical Data Translator program.
Each data type will be comprehensive (e.g., all diseases, all pathways, all SNPs). It also will be possible for a user to access the Translator for any data type and identify all connections in any other data type. This will enable a shift from the current symptom-based diagnosis of disease to one that is based on a set of molecular and cellular abnormalities and can be targeted by various preventive and therapeutic interventions.
NCATS is aware of the many existing efforts to catalogue or connect individual data types. Although these efforts provide proof of principle, the Translator will be broader in scope, with the goal of revealing potential relationships across the spectrum of data types, from signs and symptoms to molecules and drugs.
Examples of the types of queries the Translator will enable for the first time could include, but are not limited to, the following:
- Show every disease that has symptom X and/or affects a particular cell type.
- Show all molecular pathways that, when perturbed, lead to malfunction of organelle A in organ B in people with X-Y-Z genomic characteristics.
- Show all the treatments currently being investigated that perturb any pathway that is dysfunctional in diseases characterized by clinical sign X.
This effort will require unprecedentedly broad teams of experts to work together in a highly collaborative manner with active program management. Input from clinicians during the design and feasibility assessment will be critical to ensuring appropriate inclusion of clinical data.