SBIR/STTR Research Award

Machine Learning Toolkit for Academic and Grey Literature Screening

Award identifier 02091127e6a14eef268603056d7ae44cf14c095ed2b36e6567283b563f5f4aaaAwarding agency Environmental Protection Agency

Award amount

$397,332

Program and phase

SBIR · Phase II

Award year

2024

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Award details

Awarding agency
Environmental Protection Agency
Branch
Not reported
Recipient company
VISIMO LLC
Proposal award date
2023-10-19
Contract end date
2025-10-18
UEI
X854ZJDHWHJ5
Solicitation number
68HERC23R0188
Topic code
6A

Research abstract

ChemGrey, VISIMO’s machine-learning (ML) toolkit for academic and grey literature, will facilitate efficient and transparent collection, tagging, and screening of relevant sources during the systematic review (SR) process. ChemGrey will enable researchers to filter full documents of all types and formats, identify relationships between documents, determine source relevance, perform improved meta-tagging, provide accurate duplicate removal, process new inputs in real-time, and tailor the document relevancy algorithm to the needs of each researcher. By building a tool to locate and filter both academic and grey literature, VISIMO can reduce the time required to conduct SRs, increase the accuracy of SRs, and improve the reproducibility of SRs. The improvements provided by ChemGrey will strengthen the quality of SRs, increase the number of SRs conducted, and generate improvements in human and environmental health. While ChemGrey can filter academic literature, its focus is to reduce the burden of grey literature collection and screening, an often arduous process for researchers. While there are commercialized tools that address academic literature in a generalized manner, ChemGrey is document-agnostic and capable of processing grey literature just as accurately and as easily as academic literature. Identification and incorporation of additional relevant grey sources will foster more comprehensive reviews, reduce publication bias, and increase scientific integrity to ensure science-based decision making. Furthermore, ChemGrey is designed to continually optimize using feedback from the end user, allowing the tool to be tailored to the needs of each researcher. During the Phase I effort, VISIMO successfully developed a proof-of-concept (PoC) of ChemGrey with statistically significant results. During Phase II, VISIMO will further refine the ML pipeline, enhance the user interface, increase the toolkit’s transparency and interpretability, and add data gathering capabilities. VISIMO will perform iterative alpha and beta testing to continue to refine the tool, supported by researchers at multiple organizations and universities. While ChemGrey is designed to meet EPA needs for chemical risk assessments, the toolkit can be adapted to other disciplines, including medical science, food and veterinary science, agricultural science, and pharmacology.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

25 SBIR/STTR records share this UEI (2021–2025). Reported award amounts total $8,175,847. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, Department of Energy, National Aeronautics and Space Administration, Environmental Protection Agency, Department of Agriculture, Department of Commerce

Agency intelligence

Environmental Protection Agency

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