SBIR/STTR Research Award
Drug target identification using CRISPRi/a screening
Award amount
$224,455Program and phase
STTR · Phase IAward year
2020Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- BIOIO, LLC
- Proposal award date
- 2020-05-01
- Contract end date
- 2021-04-30
- UEI
- Not reported
- Solicitation number
- PA19-270
- Topic code
- 400
Research abstract
ABSTRACT
As phenotypic screening makes a comeback in drug discovery, its major issue is drug target identification.
There aren’t good generalizable approaches to do target identification for compounds of interest. Identifying
how a new drug works at the molecular level is critical for improving it, which is often needed to give it the best
chance of ultimately being both safe and effective in patients. In this proposal, we demonstrate a genome-wide
CRISPRi/a screening process in human cells that readily identifies the molecular target(s) for drugs of interest.
We present preliminary evidence it can also identify alternative targets for the disease indication for the drug as
well as potential side effect targets. We demonstrate this screening process can be applied to drugs for diverse
diseases. Thus, it has the potential to improve the number of drugs that make it through drug development
pipelines that currently have high failure rates such as those for Alzheimer’s and diabetes. In the last two
decades companies like Foundation Medicine have used genomics to make an increasing impact on disease
diagnostics in the Healthcare industry. We propose to similarly use genomics to make an impact on the
pharmaceutical industry creating a “drug diagnostics” market in the process.PROJECT NARRATIVE
Identifying how a new drug works at the molecular level is critical for refining it, which is often needed to give it
the best chance of ultimately being safe and effective in patients. In this proposal we demonstrate a genetic
screening process that can identify which genes are most important to how a drug works. Moreover, we
propose this screening process is generalizable to drugs for diverse diseases, thus potentially improving the
number of drugs that make it through Randamp;D pipelines with high failure rates such as those for Alzheimer’s and
diabetes.
Technology keywords
Not reported
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