Industry 4.0 Implementation in Continuous Pharmaceutical Manufacturing

工业 4.0 在连续制药制造中的实施

• 批准号: 10230736
• 负责人: Marianthi Ierapetritou
• 金额: $ 98.4万
• 依托单位: UNIVERSITY OF DELAWARE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10230736
• 关键词: Industry; 4.0; Implementation; Continuous; Pharmaceutical

Project Summary/Abstract. In the last decade, our Center for Structured Organic Particulate Systems (C-SOPS) team has led the development of the experimental and computational infrastructure needed to enable Quality by Design (QbD) for continuous pharmaceutical manufacturing, working very closely both with the Food and Drug Administration (FDA) and with industry. Moving forward, the future of manufacturing is the industry 4.0 paradigm, which builds upon the current manufacturing trend (industry 3.0 – digital age of automation and information) to move towards more autonomous and de-centralized decisions across the entire manufacturing supply chain. The benefits in moving in this direction are significant and industries have recognized their impact in improving reliability, security, quality and safety. This proposal, which is a conceptual component of a broad initiative led by Rutgers to establish a center of excellence in Continuous Manufacturing, leverages the existing strengths and previous work and successes at Rutgers and Purdue, to develop the next generation pharmaceutical continuous manufacturing (CM) processes in accordance with the Industry 4.0 future standard. The specific aims are: Specific Aim 1: Design and implementation of integrated data management and informatics infrastructure for next generation continuous pharmaceutical processing. Specific Aim 2: Development of process knowledge extraction strategies which utilize the informatics systems established under Aim 1 for intelligent process monitoring, fault diagnosis, material tracking and real time risk assessment. Specific Aim 3: Development and assessment of continuous process improvement strategies using the informatics infrastructure of Aim 1 and knowledge extraction strategies of Aim 2.! The result of this work will be a unique toolset necessary to (i) implement Industry 4.0 in the pharmaceutical industry, and to (ii) enable FDA to regulate such applications effectively. The integrated infrastructure for process and product informatics (as demonstrated in Rutgers and Purdue CM pilot-plants) is a critical part of the full implementation of continuous manufacturing methods for pharmaceuticals. We envision that the knowledge, products, and training emanating from this endeavor, will provide both a practical proof of concept and an implementation blueprint to pursue other, more complex applications including continuous API manufacturing, and continuous manufacturing of biomolecules. The technology transferred in this work will enable enhanced performance of the CM line thus accelerating and broadening its commercialization. Once available, the toolset developed in the proposed work should also be used by regulatory agencies for a wide range of applications, including batch manufacturing, analysis of marginal and suspect products and processes (whether substandard, contaminated, adulterated, or counterfeit), and also applications beyond drugs.

项目摘要/摘要。 在过去的十年中，我们的结构化有机颗粒系统中心（C-SOP）团队领导了 通过设计（QBD）启用质量所需的实验和计算基础设施的开发 对于连续的药物制造，与食品药品监督管理局非常紧密合作 （FDA）和行业。向前迈进，制造业的未来是行业4.0范式，该范式建造 以当前的制造趋势（行业3.0 - 自动化和信息的数字时代）移动 在整个制造供应链中做出更自主和偏心的决策。 朝这个方向移动的好处是重要的，行业已经认识到它们在改善的影响方面的影响 可靠性，安全性，质量和安全性。 该提案是罗格斯（Rutgers）领导的广泛计划的概念组成部分 连续制造业的卓越中心，利用现有的优势和以前的工作以及 罗格斯和普渡大学的成功，开发下一代药品连续制造 （CM）根据行业4.0未来标准的过程。具体目的是： 特定目的1：设计和实施集成数据管理和信息基础架构 下一代连续药物处理。 特定目的2：开发利用信息系统的过程知识提取策略 根据AIM 1建立的智能过程监控，故障诊断，材料跟踪和实时风险 评估。 特定目的3：使用持续过程改进策略的制定和评估 目标1的信息基础设施和目标2的知识提取策略2！ 这项工作的结果将是（i）在药品中实施行业4.0所需的独特工具集 行业，以及（ii）使FDA能够有效地调节此类应用。用于的集成基础架构 流程和产品信息范围（如Rutgers和Purdue CM Pilot-Plants中所示）是 全面实施用于药品的连续制造方法。我们设想 知识，产品和培训这项工作将提供实际的概念证明 以及实施蓝图，用于购买其他更复杂的应用程序，包括连续API 生物分子的制造和持续制造。这项工作中传输的技术将 实现CM线的增强性能，从而加速并扩大其商业化。一次 可用的是，在拟议的工作中开发的工具集也应由监管机构使用 应用程序范围，包括批处理制造，边际和可疑产品和流程的分析 （无论是不合格，被污染，掺假还是假冒），以及药物以外的应用。