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Development and validation of a sample-to-answer metagenomics workflow for comprehensive pathogen detection in central nervous system infections

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R44AI167334-01
Agency Tracking Number: R44AI167334
Amount: $1,928,809.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: NIAID
Solicitation Number: PA20-260
Solicitation Year: 2020
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-02-02
Award End Date (Contract End Date): 2024-01-31
Small Business Information
10 Canal Park
Cambridge, MA 02141-2249
United States
DUNS: 079354025
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (415) 374-0836
Business Contact
Phone: (617) 997-8268
Research Institution

This research will ultimately advance human health by improving the diagnosis and treatment of central
nervous system infections including meningitis and encephalitis, where the causative pathogen is not identified
in up to 50% of cases. These infections are associated with significant morbidity and mortality; therefore, rapid
and accurate diagnosis is crucial for appropriate patient management and to improve outcomes. Unfortunately,
due to the variety of organisms that can cause central nervous system infections, current standard of care
diagnostic methods suffer from long turnaround times and high false negative rates. Metagenomic next-
generation sequencing (mNGS) has emerged as a promising universal detection method for infectious
disease, enabling the simultaneous identification and characterization of viral, bacterial, and fungal pathogens
directly from the DNA/RNA present in clinical samples. However, despite the increasing adoption of molecular
diagnostics in clinical microbiology labs, mNGS has not become widespread due to its cost, turnaround time,
and the technical expertise required to produce and analyze the data. The product we are developing
addresses all of these obstacles. Galileo ONE – CSF is a sample-to-answer platform that includes all of the
reagents, controls, protocols, and software required to detect and report clinically relevant pathogens directly
from a cerebrospinal fluid (CSF) sample in ~24 hours. This platform incorporates several proprietary
technologies, including a library preparation module that reduces abundant human sequences and a
quantitative bioinformatics pipeline that increases sensitivity for sequence variants. This all-in-one bundle
allows labs to easily evaluate and adopt mNGS in their own laboratories without the need for extensive
genomics or bioinformatics expertise. During our Phase I-equivalent work, we used contrived samples to
assess the feasibility of using CSF as a sample type; the results show that we can generate high-quality
libraries and detect a representative set of pathogens in CSF using our Galileo ONE workflow, which was
initially validated on plasma. Therefore, we are ready to move into the development phase of the product
development process. In Phase II, we will perform analytical and preliminary clinical validation of the Galileo
ONE – CSF platform, complete development of CSF-specific kit controls, and perform beta testing on contrived
and clinical samples with our collaborators. This product will be the first deployed mNGS platform validated for
CSF, enabling us to take advantage of the growing market for NGS-based infectious disease diagnostics,
which is expected to reach $2.1B by 2027. Galileo ONE – CSF will empower end users, who include
researchers, reference laboratories, and pharma/biotech partners, to adopt metagenomics to address the
current gap in tools for detecting central nervous system infections.

* Information listed above is at the time of submission. *

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