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

• 批准号: 2146502
• 负责人: Nikos Passas
• 金额: $ 50万
• 依托单位: Northeastern University
• 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
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2146502&HistoricalAwards=false
• 关键词: ISN; Collaborative; Research; Financial; Network

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, 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.

该“扰乱非法供应网络运作”(D-ISN) 项目的目标是开发和评估一个网络支持的系统，该系统将确定干预点并协调利益相关者扰乱医疗产品非法流动的努力。它寻求使用协调方法来促进技术创新，包括访问关键数据、网络分析、分布式推理、识别战略干预点以及缓解方法，以破坏非法、不合格和伪造药品的流动（ISFM 贸易）。该项目将提高我们国家有效扰乱非法和假冒药品贸易的能力，以防止犯罪者采用其作案手法来规避管制，从而损害公共卫生、收入、竞争、法治并影响国家安全。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，集体努力还旨在发起有关新治理和社会控制模式的讨论，从而激励政府、私营部门和学术团体分享技能、知识和数据，以解决社会问题。社会问题的解决方案被构建到一个商业模型中，该模型可以用于处理其他类似的挑战（例如腐败、恐怖主义、气候危机、建设和平）。该项目采用犯罪学、计算机科学和药理学的多学科方法来开发一个多重网络支持的系统，该系统将识别干预点，并可用于协调利益相关者的努力，以破坏医疗产品的非法流动，创造 就问题的性质达成共识，并开发和填充数据基础设施，以有效破坏非法医疗供应链，从而最大限度地减少其造成的社会危害。具体来说，该项目将解决五个主要目标：1）使用原始数据和其他研究数据来识别犯罪性不对称性并控制 ISFM 贸易中的弱点； 2）挖掘分布式数据以推断集群和链接，并从聚合数据构建多重网络以发现 ISFM 网络的拓扑和物理属性并预测缺失的实体和实体之间的连接； 3) 使用级联故障理论发现最具影响力的故障模式，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，以将稳健、准确且廉价的化学测试纳入包括阿片类药物在内的高优先级目标（抗生素和抗感染药物）的候选名单中； 4) 使用物联网和区块链来实现高度仪器化的从生产者到患者的供应链，从而能够检测 ICM 贸易； 5) 制定多方利益相关者合作的框架和激励措施，并建立 ISFM 社会责任指数来管理响应并促进集体（非营利、私人、公共）行动。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。