Knowledge discovery and machine learning to elucidate the mechanisms of HIV activity and interaction with substance use disorder
知识发现和机器学习阐明艾滋病毒活动及其与药物滥用障碍相互作用的机制
基本信息
- 批准号:10671033
- 负责人:
- 金额:$ 41.79万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-09-30 至 2026-07-31
- 项目状态:未结题
- 来源:
- 关键词:AccidentsAcquired Immunodeficiency SyndromeAgeAlgorithmsAmphetaminesAnimalsArtificial IntelligenceBiologicalBiomedical ResearchCaringClinicalClinical TrialsCocaineCognitiveCognitive deficitsDataData AnalysesData SetDevelopmentDimensionsDiseaseDrug CombinationsDrug ModelingsDrug Side EffectsElectronic Health RecordExplosionGene ExpressionGenerationsGenesGoalsHIVHIV InfectionsHIV SeropositivityHIV-1HealthHealth StatusHighly Active Antiretroviral TherapyHumanIndividualInfrastructureIntelligenceKnowledgeKnowledge DiscoveryLiteratureLongevityMachine LearningManualsMedicalMemory LossMiningModelingNeurocognitive DeficitNeurologic EffectNeuronsOpioidOutcomeOverdosePathologyPatientsPersonsPharmaceutical PreparationsPopulationPubChemQuality of lifeResearchResearch PersonnelSeveritiesSignal TransductionSubstance Use DisorderSubstance of AbuseSuicideSystemTestingTriageUnited States Department of Veterans AffairsValidationVeteransWorkWorld Health Organizationantiretroviral therapyartificial intelligence algorithmcandidate selectionclinical developmentcomorbiditydeep learning modeldrug candidatedrug of abusedrug repurposingexperiencegene interactionhealth recordimprovedinquiry-based learningmachine learning algorithmmortalitymultiple data sourcesnetwork informaticsneuroAIDSneurotoxicneurotoxicitynext generationnovelpeerpreventprogramspublic health relevancesmall moleculetext searchingtool
项目摘要
PROJECT SUMMARY
More than 36 million people worldwide are estimated to be living with HIV infection and more than 1.2 million are
in the USA. With the introduction of highly active anti-retroviral therapy, the life span of HIV-infected individuals
has increased significantly. However, the quality of life of can be compromised owing to a range of cognitive
deficits and memory loss, commonly referred to as HIV-associated neurological disorders (HAND). HIV-infected
individuals are more likely to suffer from substance use disorder (SUD), and disproportionately suffer from high
all-cause mortality. Drugs of abuse also increase severity of HAND by several potential biological mechanisms.
HIV associated cognitive deficiencies in conjunction with SUD decrease engagement in HIV care, which fuels a
worsening downward spiral of health status. Despite intensive research, there is no approved therapy for the
treatment of HAND and particularly for the combined neurological effects of HIV and drugs of abuse.
We have developed and employed MOLIERE and AGATHA, AI-based literature mining systems that
discover novel interactions that potentially contribute to HAND. These systems also prioritize mining results to
uncover small molecules that can be tested for anti-HAND therapy. Experimental validation of MOLIERE was
achieved; four small molecules predicted by MOLIERE were shown to prevent HIV-Tat and cocaine induced
neurotoxicity. AGATHA improved MOLIERE results on a massive retroactive validation and is ready to be
deployed for wider searches that now include PubChem. In parallel, our previous efforts querying the Department
of Veterans Affairs / Veterans Informatics Network Computing Infrastructure (VINCI) with specific hypotheses
have successfully uncovered potential associations of unanticipated modifiers of HIV-associated pathologies.
Collectively, these results led us to the central goal of this proposal to develop and apply an integrative
AI-based approach to analyze biomedical datasets and Electronic Health Records to determine new
mechanisms of HIV and substanses of abuse interactions, and to discover repurposed drug candidates
to be tested for the treatment of HIV-infected SUD patients. This will be accomplished in three Aims. Aim 1
will develop a multidimensional AI-based text mining approach to explore new mechanistic connections between
HAND and substanses of abuse. This will generate new knowledge of HAND and SUD interactions, and uncover
small molecule and drug candidates that can be tested for activity against the neurotoxic insults caused by HIV
and substanses of abuse. Aim 2 will develop and apply advanced machine learning and AI algorithms to explore
health records of HIV and SUD patients. The outcome will be the development of the machine learning system
to analyze VA data and generate of signals (hypotheses) for medications or medication targets that might have
value to experimentally test for repurposing to manage HAND. Aim 3 will prioritize the selected candidates for
experimental validation and further clinical development.
项目总结
项目成果
期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Association between Haloperidol use and Risk of Rheumatoid Arthritis.
氟哌啶醇使用与类风湿关节炎风险之间的关联。
- DOI:10.1101/2023.09.11.23295367
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Ambati,VidyaL;Cummings,TammyH;Yerramothu,Praveen;Nguyen,Joseph;Sutton,SScott;Werner,BrianC;Magagnoli,Joseph
- 通讯作者:Magagnoli,Joseph
Odds of Achieving Target Serum Uric Acid Levels Among Gout Patients: The Role of Rurality in Outcomes and Treatment Adherence.
- DOI:10.1177/21501319231167379
- 发表时间:2023-01
- 期刊:
- 影响因子:3.6
- 作者:Sutton, S. Scott;Magagnoli, Joseph;Cummings, Tammy H.;Hardin, James W.
- 通讯作者:Hardin, James W.
Leukotriene receptor antagonism with montelukast as a possible therapeutic for venous thromboembolism prophylaxis: An observational study.
孟鲁司特的白三烯受体拮抗作用作为静脉血栓栓塞预防的可能治疗方法:一项观察性研究。
- DOI:10.1016/j.prostaglandins.2022.106649
- 发表时间:2022
- 期刊:
- 影响因子:2.9
- 作者:Sutton,SScott;Magagnoli,Joseph;Cummings,TammyH;Hardin,JamesW
- 通讯作者:Hardin,JamesW
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{{ truncateString('Ilya Safro', 18)}}的其他基金
Knowledge discovery and machine learning to elucidate the mechanisms of HIV activity and interaction with substance use disorder
知识发现和机器学习阐明艾滋病毒活动及其与药物滥用障碍相互作用的机制
- 批准号:
10348407 - 财政年份:2021
- 资助金额:
$ 41.79万 - 项目类别:
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