AI-driven in vivo profiling in zebrafish: a platform for alcohol use disorder therapeutic discovery
Full Description
PROJECT SUMMARY
Alcohol Use Disorder (AUD) is a pervasive condition with a substantial global burden, including considerable
morbidity, mortality, and societal impact, as well as mounting healthcare costs, lost productivity, and familial
breakdowns. However, despite the high prevalence and substantial burden of AUD, there remains a significant
unmet need in its treatment. The current therapeutic landscape for AUD includes behavioral therapies, such as
cognitive-behavioral therapy (CBT) and motivational enhancement therapy (MET), which have limited
effectiveness, and a small number of therapeutic options. A major contributor to the lack of novel pharmaceutical
treatments for AUD has been that, unlike other disorders of similar prevalence, there is an absence of scalable
models capable of performing initial hit identification. Here, we will leverage:
1. Our AI-based zebrafish behavioral screening platform which has been commercially deployed for other
disease areas,
2. Our experimental findings specific to AUD in zebrafish, and,
3. Our consortium’s extensive experience in therapeutic discovery and development,
to produce a commercial platform for AUD therapeutic development, and a proprietary novel chemical series
that can be further developed as an AUD therapeutic.
Broader Impacts
Market impacts & human health: The proposed AI platform promises a more rapid and accurate identification of
potential AUD therapeutics—reducing time, resources, and financial risks associated with the traditional drug
discovery process, and ultimately tailored specifically to AUD, an area with substantial unmet therapeutic need.
We also anticipate the identification of at least one novel chemical series using this platform, which itself
represents a separate source of protectable IP and ultimately value that can be realized upon out-licensing or
further development by our consortium.
Potential for new knowledge: By leveraging AI/ML and in vivo screening in a living vertebrate, we are building a
novel platform for therapeutic discovery that specifically quantifies behavioral, morphological, and cellular effects
relevant to the three phases of AUD: binge/intoxication, withdrawal, and chronic use.
Grant Number: 1R42AA032207-01
NIH Institute/Center: NIH
Principal Investigator: Lu Chen
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