EAGER: ISN: Unraveling Illicit Supply Chains for Falsified Pharmaceuticals with a Citizen Science Approach

EAGER：ISN：以公民科学的方式揭开假药的非法供应链

• 批准号: 1842369
• 负责人: Marya Lieberman
• 金额: $ 30万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1842369&HistoricalAwards=false
• 关键词: EAGER; ISN; Unraveling; Illicit; Supply

This EArly-concept Grant for Exploratory Research (EAGER) will advance the national health, welfare, and prosperity by studying ways to detect and disrupt the supply networks for falsified pharmaceuticals and illicit drugs. Falsified pharmaceuticals harm hundreds of thousands of patients in the developing world, as well as injuring Americans when they penetrate the U.S. pharmaceutical supply. Illicit drugs, such as opioids, are the cause of more deaths in the U.S. than automobile accidents or gun violence. Analyzing pharmaceuticals using traditional methods is time-consuming and expensive, so producers and distributors often escape discovery. This research will utilize an inexpensive paper analytic device (PAD) in the form of a test card that can be deployed by community health workers and ordinary citizens, that is capable of detecting active ingredients and fillers in a pill or powder within 5 minutes. By swiftly identifying of the types of fillers used, counterfeit pharmaceuticals or illicit drugs in several different locations can be linked, and researchers can begin to reverse engineer the supply chain to identify the source of the product and its distribution channels. Effective deployment strategies for test cards will be developed, and data visualization tools can then be provided to enable local regulatory agencies to act quickly to trace and disrupt suppliers of falsified medicines or illicit drugs. The project will involve both graduate students, focused on detection of fake medicines and supply chain vulnerabilities in low resource settings, and undergraduates, focused on detection of supply chains for illicit opioid drugs. The research will lead to models that describe the movement of products through the supply chain, suggesting pinch points or critical pathways that could be used to shut down distribution of the illicit products. Through the partnership between an analytical chemist and an operations researcher, this project will allow for timely collection and analysis of post-market pharmaceutical samples to detect a wide range of illegal practices and harmful medicines or drugs drugs. The PAD gives fast but imperfect data via the cell phone network; from an operations engineering perspective, the system offers new opportunities to dynamically retarget sample collection, optimize logistics of confirmatory analysis and interactions with regulatory authorities, and model how illicit products enter the pharmaceutical supply chain. The project will test these strategies in real-world settings. Samples of essential medicines will be collected by covert shoppers in Kenya, Malawi, and Bangladesh, and tested with PADs. Integrating methods from operations engineering, the project will test approaches for detecting active ingredients and fillers, determine the incremental value of different types of samples for understanding the supply chains of falsified medications, and examine innovative sampling methods that respond dynamically to early reports of bad quality products. The research will lead to models that describe the movement of the products through the supply chain. Students involved in this project will test samples of street drugs in a police drug lab and classify them into batches according to active ingredient and filler content, with the goal of deducing how many producers are active in the supply chains for these illegal products.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.

EARLY概念探索性研究补助金（EAGER）将通过研究如何检测和破坏伪造药品和非法药物的供应网络来促进国家健康，福利和繁荣。 假冒药品伤害了发展中国家数十万患者，并在渗透美国药品供应时伤害了美国人。 非法药物，如阿片类药物，是美国死亡人数超过汽车事故或枪支暴力的原因。使用传统方法分析药物既耗时又昂贵，因此生产商和分销商往往无法被发现。这项研究将利用一种廉价的纸分析设备（PAD），以测试卡的形式，可以由社区卫生工作者和普通公民部署，能够在5分钟内检测药丸或粉末中的活性成分和填充物。 通过快速识别所用填充剂的类型，可以将几个不同地点的假药或非法药物联系起来，研究人员可以开始对供应链进行逆向工程，以确定产品的来源及其分销渠道。 将制定有效的测试卡部署战略，然后提供数据可视化工具，使当地监管机构能够迅速采取行动，追踪和破坏假药或非法药物的供应商。 该项目将涉及研究生和本科生，研究生侧重于在低资源环境中检测假药和供应链漏洞，本科生侧重于检测非法阿片类药物的供应链。 这项研究将产生描述产品在供应链中流动的模型，提出可用于关闭非法产品分销的关键点或关键路径。通过一名分析化学家和一名业务研究员之间的伙伴关系，该项目将能够及时收集和分析上市后的药品样本，以发现各种非法做法和有害药品或毒品。 PAD通过手机网络提供快速但不完美的数据;从运营工程的角度来看，该系统提供了新的机会，可以动态地重新定位样本采集，优化验证性分析的物流和与监管机构的互动，并模拟非法产品如何进入药品供应链。该项目将在现实世界中测试这些策略。 基本药物的样品将由肯尼亚、马拉维和孟加拉国的秘密购物者收集，并使用PAD进行测试。该项目将整合运营工程的方法，测试检测活性成分和填充剂的方法，确定不同类型样品的增量价值，以了解伪造药物的供应链，并检查动态响应质量不良产品早期报告的创新抽样方法。该研究将导致描述产品在供应链中移动的模型。 参与该项目的学生将在警察毒品实验室测试街头毒品样品，并根据活性成分和填充物含量将其分类，目的是推断出这些非法产品的供应链中有多少生产商活跃。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Beyond Wax Printing: The Future of Paper Analytical Device Fabrication

• DOI: 10.1016/j.snb.2023.134059
• 发表时间: 2023-05
• 期刊: Sensors and Actuators B: Chemical
• 作者: Rachel M. Roller;M. Lieberman

Reciprocal innovation: A new approach to equitable and mutually beneficial global health partnerships

• DOI: 10.1080/17441692.2022.2102202
• 发表时间: 2022-07-26
• 期刊: GLOBAL PUBLIC HEALTH
• 影响因子: 3.3
• 作者: Sors, Thomas G.;O'Brien, Rishika Chauhan;Litzelman, Debra K.
• 通讯作者: Litzelman, Debra K.

Inferring sources of substandard and falsified products in pharmaceutical supply chains

• DOI: 10.1080/24725854.2023.2174277
• 发表时间: 2023-02-23
• 期刊: IISE TRANSACTIONS
• 影响因子: 2.6
• 作者: Wickett，Eugene;Plumlee，Matthew;Pribluda，Victor
• 通讯作者: Pribluda，Victor

Enzyme-based paper test for detection of lactose in illicit drugs

用于检测非法药物中乳糖的酶纸测试

• DOI: 10.1039/c9ay02459j
• 发表时间: 2020
• 期刊: Analytical Methods
• 影响因子: 3.1
• 作者: Zinna, Jessica;Lockwood, Tracy-Lynn E.;Lieberman, Marya
• 通讯作者: Lieberman, Marya

Discrimination of Substandard and Falsified Formulations from Genuine Pharmaceuticals Using NIR Spectra and Machine Learning

• DOI: 10.1021/acs.analchem.2c00998
• 发表时间: 2022-09-06
• 期刊: ANALYTICAL CHEMISTRY
• 影响因子: 7.4
• 作者: Awotunde, Olatunde;Roseboom, Nicholas;Lieberman, Marya
• 通讯作者: Lieberman, Marya