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COLLABORATIVE DRUG DISCOVERY, INC. SBIR Phase II Award, April 2021

A SBIR Phase II contract was awarded to Collaborative Drug Discovery in April, 2021 for $727,255.0 USD from the U.S. Department of Health & Human Services and National Institutes of Health.

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sbir.gov/node/2186927
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Collaborative Drug Discovery
Collaborative Drug Discovery
0
Government Agency
0
Government Branch
National Institutes of Health
National Institutes of Health
0
Award Type
SBIR0
Contract Number (US Government)
2R44TR002699-02A10
Award Phase
Phase II0
Award Amount (USD)
727,2550
Date Awarded
April 10, 2021
0
End Date
March 31, 2023
0
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. !PROJECT NARRATIVE The proposed project will create a novel intelligent chemistry browser that will help medicinal chemists to organize experimental data about drug candidates and select the best ones to advance to animal studies and clinical trials. This innovative new software will help to accelerate the discovery and development of novel and improved drugs – against a wide range of diseases – that are more effective and safer. !

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