grant

AI-driven in vivo profiling in zebrafish: a platform for alcohol use disorder therapeutic discovery

Organization BIOSYMETRICS, INC.Location BETHESDA, UNITED STATESPosted 1 Aug 2025Deadline 31 Jul 2026
NIHUS FederalResearch GrantFY2025AI AugmentedAI assistedAI basedAI based platformAI drivenAI enhancedAI integratedAI platformAI poweredAffectAlcohol Chemical ClassAlcoholsAmericanAreaArtificial Intelligence enhancedArtificial Intelligence platformAugmented by AIAugmented by the AIAugmented with AIAugmented with the AIBehavior Conditioning TherapyBehavior ModificationBehavior TherapyBehavior TreatmentBehavioralBehavioral Conditioning TherapyBehavioral ModificationBehavioral TherapyBehavioral TreatmentBrachydanio rerioChemicalsChronicClinicalCognition TherapyCognitive PsychotherapyCognitive TherapyCognitive treatmentComputer AnalysisConditioning TherapyDanio rerioDataDetectionDevelopmentDiseaseDisorderEffectivenessEvaluationGene Expression MonitoringGene Expression Pattern AnalysisGene Expression ProfilingGeneticHealthHealth Care CostsHealth CostsHigh PrevalenceHumanIntoxicationKnowledgeLicensingMarketingModelingModern ManMolecularMolecular FingerprintingMolecular ProfilingMorbidityMorbidity - disease rateMorphologyNeurologicNeurologicalPharmaceutical AgentPharmaceuticalsPharmacologic SubstancePharmacological SubstancePhasePhenotypePrevalenceProcessProductivityRecoveryResearch ResourcesResolutionResourcesRiskRodentRodent ModelRodentiaRodents MammalsSeriesSourceSymptomsTherapeuticTimeTranscript Expression AnalysesTranscript Expression AnalysisTranslatingValidationWithdrawalZebra DanioZebra FishZebrafishaddictionaddictive disorderalcohol abuse therapyalcohol abuse treatmentalcohol exposedalcohol exposurealcohol treatmentalcohol use disorderanalyze gene expressionartificial intelligence assistedartificial intelligence augmentedartificial intelligence basedartificial intelligence drivenartificial intelligence integratedartificial intelligence poweredbehavior interventionbehavioral interventionchemical libraryclinical applicabilityclinical applicationcognitive behavior interventioncognitive behavior modificationcognitive behavior therapycognitive behavioral interventioncognitive behavioral modificationcognitive behavioral therapycognitive behavioral treatmentcommercial applicationcomputational analysescomputational analysiscomputer analysesdetermine efficacydevelopmentaldisease modeldisorder modeldrug discoveryefficacy analysisefficacy assessmentefficacy determinationefficacy evaluationefficacy examinationenhanced with AIenhanced with Artificial Intelligenceethanol exposedethanol exposureethanol use disorderevaluate efficacyexamine efficacyexperienceexposed to alcoholexposed to ethanolexposure to alcoholexposure to ethanolgene expression analysisgene expression assayhepatoprotectionhepatoprotectivein vivolead seriesmolecular profilemolecular signaturemortalitymotivational enhancement therapymotivational interviewnew drug treatmentsnew drugsnew pharmacological therapeuticnew therapeuticsnew therapynext generation therapeuticsnovelnovel drug treatmentsnovel drugsnovel pharmaco-therapeuticnovel pharmacological therapeuticnovel therapeuticsnovel therapypharmaceuticalreduced alcohol useresolutionsscreeningscreeningssmall moleculesmall molecule librariestherapeutic agent developmenttherapeutic developmenttranscriptional profilingvalidations
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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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