在监测基本药物质量的全球南北伙伴关系中确保监管链和数据完整性。

Kathleen Hayes, Natalie Meyers, Christopher Sweet, Ayenew Ashenef, Tim Johann, Marya Lieberman, David Kochalko
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引用次数: 1

摘要

在低收入和中等收入国家(LMICs),伪劣药品约占药品供应链的10%,这些国家缺乏监管和实验室资源,限制了进行有效上市后监督的能力,并允许伪劣产品渗透到供应链中。2014年建立了分布式药物分析实验室(DPAL),以扩大对来自低收入国家的药物剂型的检测;DPAL是一个由美国和国外的学术机构组成的联盟,为来自中低收入国家合作伙伴的药物剂型提供高质量、经过验证的化学分析。分析结果报告给相关监管机构,并用于为国内利益相关者做出的采购决策提供信息。随着DPAL项目扩展到每年测试超过1000种药物剂型,数据管理和样品跟踪方面的挑战已经浮出水面。在这里,我们描述了DPAL和ARTiFACTs之间的一个试点项目,该项目应用区块链来组织和管理DPAL工作流程中生成的关键数据,包括样本在工作流程中的进度、其物理位置、元数据的来源和实验室声誉。用这些数据记录时间和日期戳将为样品创建一个永久的、可验证的监管链。这种安全的分布式账本将链接到一个易于使用的仪表板,允许利益相关者实时查看每个样本的结果和实验细节,并验证DPAL分析数据的完整性。将这种基于区块链的系统作为试点引入,将使我们能够通过真实用户分析真实样本来测试该技术。在所有DPAL站点实施区块链之前,将记录用户的反馈并对系统进行必要的调整。实施区块链技术管理DPAL数据的预期好处包括对路由工作的有效管理,提高吞吐量,为样本及其数据创建符合DPAL分布式特性的监管链,以及使用分析结果来检测产品内部和跨品牌的质量模式,并开发增强的采样技术和最佳实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Securing the Chain of Custody and Integrity of Data in a Global North-South Partnership to Monitor the Quality of Essential Medicines.

Substandard and falsified (SF) pharmaceuticals account for an estimated 10% of the pharmaceutical supply chain in low- and middle-income countries (LMICs), where a lack of regulatory and laboratory resources limits the ability to conduct effective post-market surveillance and allows SF products to penetrate the supply chain. The Distributed Pharmaceutical Analysis Laboratory (DPAL) was established in 2014 to expand testing of pharmaceutical dosage forms sourced from LMICs; DPAL is an alliance of academic institutions throughout the United States and abroad that provides high-quality, validated chemical analysis of pharmaceutical dosage forms sourced from partners in LMICs. Results from analysis are reported to relevant regulatory agencies and are used to inform purchasing decisions made by in-country stakeholders. As the DPAL program has expanded to testing more than 1,000 pharmaceutical dosage forms annually, challenges have surfaced regarding data management and sample tracking. Here, we describe a pilot project between DPAL and ARTiFACTs that applies the blockchain to organize and manage key data generated during the DPAL workflow, including a sample's progress through the workflow, its physical location, provenance of metadata, and lab reputability. Recording time and date stamps with these data will create a permanent and verifiable chain of custody for samples. This secure, distributed ledger will be linked to an easy-to-use dashboard, allowing stakeholders to view results and experimental details for each sample in real time and verify the integrity of DPAL analysis data. Introducing this blockchain-based system as a pilot will allow us to test the technology with real users analyzing real samples. Feedback from users will be recorded and necessary adjustments will be made to the system before the implementation of blockchain across all DPAL sites. Anticipated benefits of implementing the blockchain technology for managing DPAL data include efficient management for routing work, increasing throughput, creating a chain of custody for samples and their data in alignment with the distributed nature of DPAL, and using the analysis results to detect patterns of quality within and across brands of products and develop enhanced sampling techniques and best practices.

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