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-SOPS)团队领导了 开发实现按设计提供质量(QBD)所需的实验和计算基础设施 对于持续的制药生产，与食品和药物管理局密切合作 (FDA)和工业界。展望未来，制造业的未来是行业4.0范式，它构建了 根据当前的制造业趋势(工业3.0-自动化和信息的数字时代)移动 在整个制造业供应链中朝着更加自主和分散决策的方向发展。这个 朝这个方向前进的好处是显著的，各行业已经认识到它们在改进方面的影响 可靠性、安全性、质量和安全性。 这项提案是罗格斯大学领导的一项广泛倡议的概念组成部分，该倡议旨在建立 卓越的连续制造中心，利用现有的优势和以前的工作 罗格斯和普渡的成功，发展下一代制药连续制造 (Cm)符合行业4.0未来标准的流程。具体目标是： 具体目标1：设计和实施综合数据管理和信息基础设施 下一代连续制药工艺。 具体目标2：制定利用信息学系统的工艺知识提取战略 根据目标1设立，用于智能流程监测、故障诊断、材料跟踪和实时风险 评估。 具体目标3：开发和评估持续过程改进战略，使用 目标1的信息学基础设施和目标2的知识抽取策略。 这项工作的结果将是(I)在制药行业实施行业4.0所必需的独特工具集 (Ii)使FDA能够有效地监管此类应用。集成的基础设施 过程和产品信息学(如罗格斯大学和普渡大学的CM试点项目所展示的)是 全面推行药品连续生产办法。我们设想， 从这一努力中产生的知识、产品和培训将提供概念的实际证明 以及实施蓝图，以追求其他更复杂的应用程序，包括连续API 生物分子的制造和连续制造。这项工作中转让的技术将 增强CM生产线的性能，从而加速和扩大其商业化。一次 可用，在拟议的工作中开发的工具集也应被监管机构广泛使用 应用范围广泛，包括批量制造、分析边缘产品和可疑产品和流程 (无论是不合格的、受污染的、掺假的或假冒的)，以及药物以外的应用。