The goal of this proposal is to dramatically improve speed and accuracy in clinical decision-making for patients requiring a genetic diagnosis. Next generation sequencing (NGS) technology has revolutionized the clinical practice of diagnosing rare genetic diseases and has the potential to become standard practice across many medical disciplines. The single most intractable challenge is that current practices for the analysis of sequenced genetic variants require an exorbitant amount of manual analysis by skilled biomedical professionals; this human time requirement is incapable of scaling with NGS volume. The proposed product, SolveBio's Variant Explorer (VE), is a cloud- based graphical software system that assists in variant interpretation, or the ascertaining of the clinical significance of sequenced genetic variant. The VE aims to alleviate the analysis problem by guiding and removing manual analysis steps. The technical innovation lies in SolveBio's proprietary data infrastructure and a prioritization on usability. SolveBio's core technology is a programmatic and scalable data pipeline that performs the parsing, normalizing, and versioning of genomic reference data. SolveBio also prioritizes user interaction and experience, a focus that is commonly lacking in bioinformatics tools. The long-term goal of this project is to exponentially improve speed, accuracy, and efficiency in genetic variant analysis so that patients suffering from genetic diseases suitable for NGS-based analyses receive timely, cost-efficient, and accurate results. Our Phase I hypothesis is that SolveBio's reference data infrastructure and user-oriented design will systematically reduce and streamline the manual analysis steps in variant interpretation.
Our aims are to algorithmically bring together all known and possible notations for a specific variant and to build and design a relevant literature collation and rankin system. Our Phase II objectives will consist of building out the VE into a modular and complete data analysis solution with a variant classifier capable of assigning a preliminary clinical significance to each variant. NGS-based diagnostics are projected to grow tenfold in market size over the next 5-10 years. SolveBio's Variant Explorer will help unclog the analysis bottleneck and pave the way for widespread adoption of NGS-based technology and the realization of precision medicine.

Public Health Relevance

In this Phase I SBIR, SolveBio plans to develop a cloud-based software system that combines disparate and complex reference databases to improve efficiency and accuracy in analyzing how sequenced genetic variants cause genetic diseases. This research will provide solutions for faster and more accurate genetic diagnoses and ultimately support the development of precision medicine.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-HDM-R (11)B)
Program Officer
Ravichandran, Veerasamy
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Solve, Inc.
New York
United States
Zip Code