SBIR/STTR Research Award

Intelligent Chemical Structure Browser for Drug Discovery and Optimization

Award identifier 4d583a82a9bf24d8056a4b790b703e03bb6bcc42584c9239f6e9d0c265095757Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,454,510

Program and phase

SBIR · Phase II

Award year

2021

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
COLLABORATIVE DRUG DISCOVERY, INC.
Proposal award date
2021-04-10
Contract end date
2023-03-31
UEI
KC1DAXHM8424
Solicitation number
PA20-260
Topic code
100

Research abstract

PROJECT SUMMARY Collaborative Drug Discovery, Inc. (CDD) proposes to develop a novel intelligent data browser that will enable medicinal chemists developing new drug compounds to more efficiently browse and organize experimental data in an intuitive way. The proposed browser will essentially “hyperlink” chemical space and allow chemists to navigate easily among compounds in a chemical lead series following the same pathways that lead from one compound to the next in the mental models that they intuitively map in their heads. Navigating through and extending a lead series to discover the optimal drug candidate to advance into animal studies and clinical trials comprises a critical stage of the drug discovery pipeline: the success of large subsequent investments depends on making the right decision. This stage also especially emphasizes creative and intuitive thinking. Existing software that assists scientists engaged in this task tabulates data in formats that make it difficult to assemble and compare the essential data needed to rapidly explore ideas about how to further optimize promising candidates. Our proposed intelligent browser will support more natural and intuitive workflows.A key enabling innovation for this technology is a methodology that we have developed to organize molecular structures through a partial ordering based on the substructure-superstructure relation as a Hasse diagram. Our semilattice representation provides a machine computable format that can capture the relationships among related chemical entities that a medicinal chemist intuits.Expected key impacts include (1) faster development of lead series into drug candidates, (2) cost savings due to more efficient use of synthesis and assay resources, and most importantly (3) better scientific decisions about which compounds to pursue and advance into the clinical pipeline. Better decisions at this stage in the drug discovery process should increase the probability that drug candidates that are chosen will successfully emerge through the clinical pipeline as FDA approved drugs, and improve the effectiveness and safety profile of those drugs. Even a small increase in these probabilities multiplied by the size of the investments required to take drugs through clinical trials translates into a large value. We have validated this perception of value in preliminary market research with potential pharmaceutical company customers. !

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

17 SBIR/STTR records share this UEI (2010–2022). Reported award amounts total $14,412,575. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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