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Translator Frequently Asked Questions


What are NCATS’ goals for the Biomedical Data Translator program?

The long-term goal is to accelerate translation through the development of a biomedical data translator for the research community. NCATS envisions this as a multiyear, iterative effort with the eventual 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. Each data type (see Appendix of FY 2016 Funding Opportunity Announcement (PDF - 134KB) for examples) must be comprehensive (e.g., all diseases, all pathways, all SNPs). It must be possible for a user to access the Translator from any data type and identify all connections in any other data type. In doing so, NCATS will enable a shift from the current symptom-based disease diagnosis to disease classification that is based on a set of molecular and cellular abnormalities that can be targeted by various preventative and therapeutic interventions..

Why has NCATS created this program?

NCATS created the Biomedical Data Translator program to address some of the biggest challenges in translational science. The different approaches taken and scientific language used by physicians and biomedical researchers can act as roadblocks in the translational path. NCATS takes a disease-agnostic approach toward addressing translational science, providing an interdisciplinary perspective that cuts across scientific boundaries and disease/organ system silos. Such a perspective is necessary to remove those roadblocks and help bring more treatments to more patients more quickly.

What are the anticipated outcomes of the awards made in 2016

Awardees will identify high-value data sources that would be needed for a comprehensive Biomedical Data Translator and design the infrastructure that would be needed to integrate those data. Expected goals for those projects include:

  • Identifying high-value data sources that should be included in a comprehensive Translator and a means to evaluate validity and utility of those data;
  • Developing a plan for integrating across a comprehensive variety of data types;
  • Identifying integration barriers (e.g., entity recognition, entity resolution, entity stitching, etc.) or data inclusion barriers;
  • Developing and testing a plan for data quality control;
  • Developing a demonstration project that illustrates innovative integration of as many disparate data types as possible (novel integration of different data types being more important than the number of data types integrated); and
  • Defining the requirements for a comprehensive Translator, including its architecture and development path that will catalyze getting more treatments to more patients more quickly.

Are non-awardees able to participate in the NCATS-organized quarterly workshops with the intent of learning more about challenges in this effort and identifying means of partnering on possible solutions?

While awardees are required to participate in the quarterly workshops, non-awardees may be invited by NCATS to participate.

What types and sources of data will be included in the Biomedical Data Translator? Who will identify those data types and sources?

The Biomedical Data Translator will integrate 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. Each data type must be comprehensive (e.g., all diseases, all pathways, all SNPs). In the technical feasibility assessment and architecture design phase of the Translator program, the awardees will identify high-value data sources that would be needed for a comprehensive Translator, as well as a means to evaluate the validity and utility of those data.

Will software written as part of this program be open source?

NCATS expects that this project will be intensely collaborative among research partners and NIH staff, and that the unrestricted exchange of source code and software tools written as part of this program will be essential to a successful outcome. The goal of this programmatic effort is to produce data, software and tools that are completely publicly available for any user, without requirement to subscribe to proprietary resources or tools to be used.

Last updated: 09-26-2017
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