Development of the AI-driven model for anti-SUD drug development based on neuronal plasticity
基于神经元可塑性的人工智能驱动抗SUD药物开发模型的开发
基本信息
- 批准号:10467528
- 负责人:
- 金额:$ 31.23万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-04-01 至 2023-09-30
- 项目状态:已结题
- 来源:
- 关键词:AbstinenceAdderallAddressAffectAftercareAgonistAlgorithmsAmericanAnhedoniaAnimal ModelAnimal TestingAnimalsAreaArtificial IntelligenceArtificial Intelligence platformBehavior TherapyBlood - brain barrier anatomyBrainCOVID-19 pandemicChemicalsClinicalCocaineComputer ModelsCustomDescriptorDevelopmentDoseDrug CompoundingDrug KineticsDrug TargetingDrug TransportEnvironmentEvaluationFDA approvedGenerationsGoalsHeelHumanHybridsIndividualInfrastructureInpatientsIntravenousInvestigational DrugsInvestmentsLegal patentLibrariesLifeLigandsLiteratureMachine LearningMedicalMethamphetamineModalityModelingNeuronal PlasticityNeurotransmittersOutcomePermeabilityPharmaceutical PreparationsPharmacodynamicsPharmacologic SubstancePharmacologyPharmacotherapyPhasePhysiologicalProcessPropertyProtein Phosphatase 2A Regulatory Subunit PR53Rehabilitation therapyRelapseReportingScientistSelf AdministrationSmall Business Innovation Research GrantSoftware EngineeringStimulantSurveysSystemTechnologyTherapeuticToxic effectTreatment CostValidationabuse liabilityagedantagonistartificial intelligence algorithmbaseblood-brain barrier penetrationclinical predictorscocaine usecompliance behaviorcostdesigndrug developmentdrug discoverydrug distributionhypocretinin silicoin vivoinnovationlead optimizationmachine learning modelmodel developmentmodels and simulationneuropharmacologic agentopioid epidemicopioid use disorderoverdose deathpharmacokinetic modelpharmacokinetics and pharmacodynamicsphysiologically based pharmacokineticspre-clinicalpredictive modelingprescription stimulantsprimary outcomeprogramsscreeningsimulationsmall moleculestimulant usestimulant use disordertherapeutic targettoolvirtualvirtual screening
项目摘要
PROJECT SUMMARY
Rates of stimulant use, both illicit (e.g. methamphetamine and cocaine) and prescription (e.g.
Adderall) are surging on the heels of the opioid epidemic, worsened by the isolation associated
with the COVID-19 pandemic. Unlike opioid use disorder, there are currently no FDA-approved
medications for the treatment of stimulant use disorder (StUD), leaving only abstinence support
and behavioral modification therapies. These are costly treatments with poor efficacy, as
evidenced by the high rate of relapse (60-90%). Stimulant use disorder is clearly an unmet need.
VeriSIM Life is an innovative company developing and utilizing artificial intelligence (AI) and
machine learning (ML) technologies for faster drug discovery and development. Our patented
BIOiSIM platform enables prediction of small molecule pharmacokinetics and pharmacodynamics
via an AI/ML-parameterized whole-body physiologically based modelling. It is designed to
accurately predict the clinical value of investigational drugs before human trials. The full-stack AI-
enabled bio-simulation models significantly reduce the number of animal tests required for
advancing therapeutics through the pipeline, accelerating drug development and markedly
increasing return on investment. The primary goal of this SBIR application is to develop, validate
and utilize a reliable and accurate AI-driven tool incorporated with the core BIOiSIM platform to
accelerate discovery and development of pharmaceuticals intended for the mitigation of StUD.
The current Phase I proposal will begin to address this goal through two complementary
approaches. Development of the AI-driven pharmacokinetic modeling specific to CNS drug
distribution with the following screening of virtual compound libraries will be performed in Aim 1.
This will be supported by proof-of-concept validation of a subset of compounds with in vivo
pharmacokinetics. Aim 2 will focus on development of pharmacodynamics prediction modeling
for stimulant use disorder drug discovery and development. The focus will be on potential
therapeutic targets that modulate neuronal plasticity, identified through an in-depth analysis of the
preclinical and clinical literature. This will be supported by proof-of-concept validation of a subset
of compounds with preclinical intravenous self-administration studies using cocaine and
methamphetamine. The proposed AI/ML-driven approach is expected to markedly accelerate the
development process for new stimulant use disorder medications by directing efforts to
compounds with optimal ADME and pharmacodynamic properties. Such an approach will create
an avenue for fast-track development of affordable and efficacious therapeutics for StUD among
other indications.
项目概要
兴奋剂的使用率,包括非法兴奋剂(例如甲基苯丙胺和可卡因)和处方兴奋剂(例如毒品)
阿德拉)紧随阿片类药物的流行而激增,而相关的隔离又加剧了这种流行
随着 COVID-19 大流行。与阿片类药物使用障碍不同,目前尚无 FDA 批准的药物
治疗兴奋剂使用障碍 (StUD) 的药物,只留下戒酒支持
和行为矫正疗法。这些治疗方法费用昂贵,但疗效不佳,
高复发率(60-90%)就证明了这一点。兴奋剂使用障碍显然是一个未满足的需求。
VeriSIM Life 是一家开发和利用人工智能 (AI) 的创新公司
机器学习 (ML) 技术可加快药物发现和开发速度。我们的专利
BIOiSIM 平台可预测小分子药代动力学和药效学
通过人工智能/机器学习参数化全身生理学建模。它的设计目的是
在人体试验前准确预测研究药物的临床价值。全栈AI——
启用的生物模拟模型显着减少了所需的动物试验数量
通过管道推进治疗方法,加速药物开发并显着
增加投资回报。该 SBIR 应用程序的主要目标是开发、验证
并利用与核心 BIOiSIM 平台相结合的可靠、准确的人工智能驱动工具
加速发现和开发用于缓解 StuD 的药物。
目前的第一阶段提案将开始通过两个互补的项目来实现这一目标
接近。开发针对中枢神经系统药物的人工智能驱动药代动力学模型
目标 1 将进行分发以及虚拟化合物库的以下筛选。
这将得到体内化合物子集的概念验证验证的支持
药代动力学。目标 2 将重点开发药效预测模型
用于兴奋剂使用障碍药物的发现和开发。重点将放在潜力上
通过深入分析确定调节神经元可塑性的治疗靶点
临床前和临床文献。这将通过子集的概念验证验证来支持
使用可卡因进行临床前静脉自我给药研究的化合物
甲基苯丙胺。所提出的人工智能/机器学习驱动方法预计将显着加速
新的兴奋剂使用障碍药物的开发过程
具有最佳 ADME 和药效学特性的化合物。这种方法将创建
快速开发经济实惠且有效的 STUD 疗法的途径
其他指示。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Courtney A Miller其他文献
Neurocranial growth in the OIM mouse model of osteogenesis imperfecta
OIM 成骨不全小鼠模型的神经颅骨生长
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Tooba S Husain;Jacob C Moore;Lila A Huston;Courtney A Miller;Ashley T Steele;Lauren A Gonzales;Emma K Handler;J. M. Organ;Rachel A Menegaz - 通讯作者:
Rachel A Menegaz
Targeting the cytoskeleton as a therapeutic approach to substance use disorders
靶向细胞骨架作为物质使用障碍的治疗方法
- DOI:
10.1016/j.phrs.2024.107143 - 发表时间:
2024-03-01 - 期刊:
- 影响因子:9.3
- 作者:
Surya P;ey;ey;Courtney A Miller - 通讯作者:
Courtney A Miller
Courtney A Miller的其他文献
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{{ truncateString('Courtney A Miller', 18)}}的其他基金
Developing nonmuscle myosin II inhibitors for the treatment of glioblastoma
开发用于治疗胶质母细胞瘤的非肌肉肌球蛋白 II 抑制剂
- 批准号:
10524193 - 财政年份:2021
- 资助金额:
$ 31.23万 - 项目类别:
Developing nonmuscle myosin II inhibitors for the treatment of glioblastoma
开发用于治疗胶质母细胞瘤的非肌肉肌球蛋白 II 抑制剂
- 批准号:
10595852 - 财政年份:2021
- 资助金额:
$ 31.23万 - 项目类别:
Developing nonmuscle myosin II inhibitors for the treatment of glioblastoma
开发用于治疗胶质母细胞瘤的非肌肉肌球蛋白 II 抑制剂
- 批准号:
10557160 - 财政年份:2021
- 资助金额:
$ 31.23万 - 项目类别:
Impact of prenatal opioid exposure on long-range brain circuit connectivity and behavior
产前阿片类药物暴露对长程脑回路连接和行为的影响
- 批准号:
10163154 - 财政年份:2020
- 资助金额:
$ 31.23万 - 项目类别:
Impact of prenatal opioid exposure on long-range brain circuit connectivity and behavior
产前阿片类药物暴露对长程脑回路连接和行为的影响
- 批准号:
10060057 - 财政年份:2020
- 资助金额:
$ 31.23万 - 项目类别:
Myosin II regulation of actin dynamics and the selective vulnerability of methamphetamine- and opioid-associated memory
肌球蛋白 II 调节肌动蛋白动力学以及甲基苯丙胺和阿片类药物相关记忆的选择性脆弱性
- 批准号:
9916255 - 财政年份:2019
- 资助金额:
$ 31.23万 - 项目类别:
Myosin II regulation of actin dynamics and the selective vulnerability of methamphetamine- and opioid-associated memory
肌球蛋白 II 调节肌动蛋白动力学以及甲基苯丙胺和阿片类药物相关记忆的选择性脆弱性
- 批准号:
10533792 - 财政年份:2019
- 资助金额:
$ 31.23万 - 项目类别:
Myosin II regulation of actin dynamics and the selective vulnerability of methamphetamine- and opioid-associated memory
肌球蛋白 II 调节肌动蛋白动力学以及甲基苯丙胺和阿片类药物相关记忆的选择性脆弱性
- 批准号:
10596356 - 财政年份:2019
- 资助金额:
$ 31.23万 - 项目类别:
Integrated Platform for Discovery and Validation of Probes that Restore Protein Expression in Single-Gene Causes of Autism and Related Disorders
用于发现和验证可恢复自闭症及相关疾病单基因病因中蛋白质表达的探针的综合平台
- 批准号:
10371224 - 财政年份:2017
- 资助金额:
$ 31.23万 - 项目类别:
Integrated Platform for Discovery and Validation of Probes that Restore Protein Expression in Single-Gene Causes of Autism and Related Disorders
用于发现和验证可恢复自闭症及相关疾病单基因病因中蛋白质表达的探针的综合平台
- 批准号:
10597839 - 财政年份:2017
- 资助金额:
$ 31.23万 - 项目类别:
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