D-ISN/Collaborative Research: Financial and Network Disruptions in Counterfeit and Illegal Medicines Trade

D-ISN/合作研究:假冒和非法药品贸易中的财务和网络中断

基本信息

  • 批准号:
    2146335
  • 负责人:
  • 金额:
    $ 25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-08-01 至 2026-07-31
  • 项目状态:
    未结题

项目摘要

The objective of this Disrupting Operations of Illicit Supply Networks (D-ISN) project is to develop and evaluate a network-enabled system that will identify points of intervention and coordinate stakeholders' efforts to disrupt illicit flows of medical products. It seeks to catalyze technological innovations using a coordinated approach that includes access to critical data, network analysis, distributed inference, identification of strategic points of intervention, and mitigation approaches to disrupt the flow of illegal, substandard, and falsified medicines (ISFM trade). The project will advance our Nation's ability to effectively disrupt trade in illicit and counterfeit pharmaceuticals to prevent offenders from adapting their modus operandi to circumvent controls and consequently undermine public health, revenue, competition, the rule of law, and impact national security. The research team's collaboration with industry and law enforcement agencies will facilitate an interactive process regarding disruption techniques. In addition, the collective effort is designed to launch discussions about new governance and social control models whereby government, private sector, and academic parties are motivated to share skills, knowledge, and data towards solving social problems. The solution to a social problem is built into a business model, which can serve in the handling of other similar challenges (e.g., corruption, terrorism, climate crisis, peacebuilding).The project employs a multidisciplinary set of methods from criminology, computer science, and pharmacology to develop a multiplex network-enabled system that will identify points of intervention and can be used to coordinate efforts of stakeholders to disrupt illicit flows of the medical product, create consensual knowledge on the nature of the problem, and develop and populate a data infrastructure to disrupt illegal medical supply chains effectively so as to minimize the social harm they cause. Specially, this project will address five primary objectives: 1) use original and other research data to identify criminogenic asymmetries and control weaknesses in the ISFM trade; 2) mine distributed data to infer clusters and linkages, and construct a multiplex network from our aggregated data to discover topological & physical properties of ISFM networks and predict missing entities and connections between entities; 3) discover the most impactful failure modes using the cascading failures theory and validate the intervention strategy by extending the microfluidic, optical and quantitative testing platform (similar to PharmaChk) to incorporate robust, accurate, but inexpensive chemical tests for a shortlist of high-priority targets (antibiotics and anti-infectives) including opioids; 4) use internet of things and blockchain to enable highly instrumented producer-to-patient supply chains that enable detection of ICM trade; and 5) develop a framework and incentives for multi-stakeholder collaboration, and build a Social Accountability on ISFM Index to manage responses and enable collective non-profit, private, and public action.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
非法供应网络(D-ISN)项目的这种破坏操作的目的是开发和评估一个支持网络的系统,该系统将确定干预点并协调利益相关者在破坏医疗产品的非法流动的努力。它试图使用协调的方法来催化技术创新,其中包括访问关键数据,网络分析,分布式推理,识别干预措施的战略点以及减轻方法,以破坏非法,不合格和伪造药物的流动(ISFM贸易)。该项目将提高我们国家有效破坏非法和伪造药物的贸易的能力,以防止罪犯适应其作案手法以规避控制,从而破坏公共卫生,收入,竞争,法治和影响国家安全。研究团队与行业和执法机构的合作将促进有关破坏技术的互动过程。此外,集体努力旨在启动有关新治理和社会控制模式的讨论,政府,私营部门和学术团队有动力分享技能,知识和数据以解决社会问题。 The solution to a social problem is built into a business model, which can serve in the handling of other similar challenges (e.g., corruption, terrorism, climate crisis, peacebuilding).The project employs a multidisciplinary set of methods from criminology, computer science, and pharmacology to develop a multiplex network-enabled system that will identify points of intervention and can be used to coordinate efforts of stakeholders to disrupt illicit flows of the medical product, create关于问题性质的共识知识,并开发和填充数据基础架构,以有效地破坏非法医疗供应链,以最大程度地减少它们造成的社会伤害。特别是,该项目将解决五个主要目标:1)使用原始和其他研究数据来识别ISFM贸易中的犯罪不对称和控制弱点; 2)矿山分布式数据以推断群集和链接,并从我们的汇总数据中构建一个多重网络,以发现ISFM网络的拓扑和物理属性,并预测实体之间的缺失实体和连接; 3)使用级联故障理论发现最有影响力的故障模式,并通过扩展微流体,光学和定量测试平台(类似于Pharmachk)来验证干预策略,以融合强大的,准确但较小的化学测试,以使高优化靶标(包括抗生素和抗生素)的短列表(包括OpioIsioss),包括opioidioidess; 4)使用物联网和区块链来启用高度仪器的生产者到患者的供应链,以实现ICM贸易的检测; 5)为多利益相关者协作开发框架和激励措施,并在ISFM索引上建立社会问责制,以管理响应,并使集体非营利性,私人和公共行动能够进行。该奖项反映了NSF的法定任务,并被认为是通过基金会的知识分子功能和广泛的影响来评估CRITERIA CRITERIA的评估。

项目成果

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Ioannis Kakadiaris其他文献

AI-enabled Cardiac Chambers Volumetry and Calcified Plaque Characterization in Coronary Artery Calcium (CAC) Scans (AI-CAC) Significantly Improves on Agatston CAC Score for Predicting All Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis
冠状动脉钙 (CAC) 扫描 (AI-CAC) 中支持 AI 的心室容量和钙化斑块特征显着改善 Agatston CAC 评分,用于预测所有心血管事件:动脉粥样硬化的多种族研究
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. Naghavi;A. Reeves;K. Atlas;Chenyu Zhang;T. Atlas;C. Henschke;D. Yankelevitz;M. Budoff;Dong Li;Sion Roy;Khurram Nasir;Jagat Narula;Ioannis Kakadiaris;S. Molloi;Zahi Fayad;David Maron;Michael McConnell;Kim Williams;Daniel Levy;Nathan S Wong
  • 通讯作者:
    Nathan S Wong

Ioannis Kakadiaris的其他文献

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{{ truncateString('Ioannis Kakadiaris', 18)}}的其他基金

NSF Convergence Accelerator Track J: Artificial-Intelligence-Based Decision Support for Equitable Food and Nutrition Security in the Houston Area
NSF 融合加速器轨道 J:基于人工智能的决策支持,实现休斯顿地区公平的粮食和营养安全
  • 批准号:
    2236305
  • 财政年份:
    2022
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
SCC-CIVIC-FA Track B: Artificial-Intelligence-Based Decision Support for Equitable and Resilient Food Distribution during Pandemics and Extreme Weather Events
SCC-CIVIC-FA 轨道 B:基于人工智能的决策支持,在大流行和极端天气事件期间实现公平和有弹性的粮食分配
  • 批准号:
    2133352
  • 财政年份:
    2021
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
SCC-CIVIC-PG Track B: Equitable Food-Security: Disaster-resilient supply chains for pandemics and extreme weather events
SCC-CIVIC-PG 轨道 B:公平粮食安全:应对流行病和极端天气事件的抗灾供应链
  • 批准号:
    2043988
  • 财政年份:
    2021
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
Supporting Student Development Activities at the International Joint Conference on Biometrics (IJCB2020)
在国际生物识别联合会议(IJCB2020)上支持学生发展活动
  • 批准号:
    2038085
  • 财政年份:
    2020
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
D-ISN: TRACK 2: Collaborative Research: Financial Network Disruptions in Illicit and Counterfeit Medicines (FIND-M)
D-ISN:轨道 2:合作研究:非法和假冒药品的金融网络中断 (FIND-M)
  • 批准号:
    2039946
  • 财政年份:
    2020
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
I-Corps: Exploiting matching score distributions to improve biometric recognition
I-Corps:利用匹配分数分布来提高生物特征识别
  • 批准号:
    1561151
  • 财政年份:
    2015
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
Segmentation of 3D Tubular Structures
3D 管状结构的分割
  • 批准号:
    0638875
  • 财政年份:
    2006
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
Collaborative Research: Physics-Based Modeling and Simulation for Post-Mastectomy Breast Reconstructive Surgery
合作研究:基于物理的乳房切除术后乳房重建手术建模与仿真
  • 批准号:
    0402591
  • 财政年份:
    2004
  • 资助金额:
    $ 25万
  • 项目类别:
    Continuing Grant
SEI: Cardiovascular Informatics
SEI:心血管信息学
  • 批准号:
    0431144
  • 财政年份:
    2004
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
2003 Workshop on Robotics and Computer Vision: PI Meeting
2003 年机器人和计算机视觉研讨会:PI 会议
  • 批准号:
    0334822
  • 财政年份:
    2003
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant

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