课题基金 / 基金详情

EAGER: Cybermanufacturing: Advanced Modeling and Information Management in Pharmaceutical Manufacturing

EAGER: Cybermanufacturing: Advanced Modeling and Information Management in Pharmaceutical Manufacturing
EAGER:网络制造:药品制造中的高级建模和信息管理
批准号:
1547171
负责人:
Marianthi Ierapetritou
金额:
$28.42万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2018-06-30

项目摘要

项目成果

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中文摘要
翻译
该项目的总体目标是利用网络基础设施(CI)的进步,开发一个数据支持的计算框架,用于有效设计和改进制药过程的操作。目前,制药行业的产品/工艺设计主要以经验方式进行,主要依靠启发式实验——因此,FDA在关键路径倡议中提出了向更多的质量设计(Qbd)范式过渡的警告。为了使这种基于qbd的决策实际适用于制药行业,需要一个健壮的计算框架。提议的框架将允许高保真仿真、实验数据和物理传感器与运行时系统的无缝集成,该系统支持在先进的计算平台上动态执行模型仿真、验证和改进。智力价值:在这些考虑的推动下,这项工作将针对以下具体目标:1)CI支持集成生产线的多尺度过程建模;2)中试设备模型集成与多尺度模型实时细化。通过NSF-ERC向pi提供结构化有机颗粒系统的试验工厂,并将允许在现实环境中进行验证和测试。这项工作将导致几个理论进展,即:1)开发混合器-造粒机过程的多尺度模型的有效方法,以及2)将开发模型与物理传感器和过程、实验数据以及强大的计算框架相结合的策略。所提出的方法将为决策者提供灵活的解决方案,因为他们可以利用开发的框架作为虚拟实验工具包,在实际工厂实施之前,在计算机上执行假设场景,以获得最佳操作条件。更广泛的影响:研究结果可用于提高许多处理颗粒过程的行业的盈利能力和可持续性,从而直接影响美国经济,包括食品,制药和化学工业。项目期间开发的软件原型和问题解决方案库将提供给该领域的其他研究人员使用和改进。pi将把研究成果整合到当前的本科设计课程中。这将使高年级学生不仅可以研究当前的化学/生化问题,还可以研究与罗格斯大学周围主要以微粒为基础的行业相关的问题,这些行业对新泽西州的经济至关重要。Jha副主任还将在欧洲经委会开设一门名为“高级高性能和分布式计算”的新选修课,并将研究问题和发现作为案例研究。pi将与参与本提案的工业合作者合作,以获得与工业高度相关的现实案例研究,从而提高即将毕业的高年级学生的就业能力。为了鼓励代表性不足的群体,pi还将与罗格斯大学(Rutgers)的少数族裔协会(全国黑人工程师协会)和道格拉斯妇女科学研究所(Douglas Science Institute for Women)合作,这些协会已经建立了一些项目,以便在研究生阶段招募合格的女性和少数族裔学生。
英文摘要
Ierapetritou, 1547171The overall objective of this project is to develop a data-enabled computational framework for the efficient design and improved operation of pharmaceutical processes using advances in cyberinfrastructure (CI). At present, product/process design in the pharmaceutical industry is largely performed in an empirical manner relying primarily on heuristic experimentation - hence the alarm raised by the FDA in the Critical Path Initiative to transition toward a more Quality-by-Design (Qbd) paradigm. For such QbD-based decision making to be practically applicable in the pharmaceutical industry, a robust computational framework is required. The proposed framework will allow the seamless integration of high-fidelity simulations, experimental data and physical sensors with a runtime system that supports the dynamic execution of model simulations, validation and refinement, on advanced computing platforms.Intellectual Merit :Motivated by the these considerations, this work will target the following specific aims: 1) CI enabled multi-scale process modeling of an integrated production line; and 2) model integration within a pilot-plant experimental facility and real-time refinement of the multi-scale model. A pilot plant available to the PIs via the NSF-ERC on structured organic particulate systems and will allow the validation and testing in a realistic setting. The work should lead to several theoretical advances namely: 1) an efficient method to develop a multi-scale model of a mixer-granulator process, and 2) strategies to integrate developed models with physical sensors and processes, experimental data, in combination with a robust computational framework. The proposed approach will result in flexible solutions for decision-makers as they can utilize the developed framework as a virtual experimental toolkit to perform what-if-scenarios in silico to obtain optimal operating conditions, prior to implementation in the real plant. Broader Impacts :Research findings can be used to enhance the profitability and sustainability of many industries that deal with particulate processes, thus directly impacting the US economy including food, pharmaceutical, and chemical industries. Software prototypes and a library of solutions to problems developed during the project will be made available for other researchers in the field to use and improve upon. The PIs will integrate research findings into the current undergraduate design course. This will enable seniors to not only work on current chemical/biochemical problems but also on problems relevant to the predominantly particulate-based industries that surround Rutgers and are critical to the New Jersey economy. Co-PI Jha will also introduce a new elective in ECE titled "Advanced High-Performance and Distributed Computing" and will use research problems and findings as case-studies. The PIs will work with industrial collaborators involved in this proposal to obtain realistic case studies that are highly industrially relevant, thereby increasing the employability of the graduating senior class. To encourage under represented groups, the PIs will also work with minority societies within Rutgers, (National Society of Black Engineers), and the Douglas Science Institute for Women, which have established programs in place, to expose and thereafter recruit qualified women and minority students at the graduate level.
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会议论文
FMRG: Eco: A Systems-Enabled Paradigm Shift for Modular Sustainable Chemical Manufacturing
  • 批准号:
    2134471
  • 项目类别:
    Standard Grant
  • 资助金额:
    $300.0万
  • 财政年份:
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  • 负责人:
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  • 批准号:
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  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
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SusChem Collaborative Research: Process Optimization of Novel Routes for the Production of bio-based Para-Xylene
  • 批准号:
    2005905
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $20.24万
  • 财政年份:
    2019
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  • 依托单位:
SusChem Collaborative Research: Process Optimization of Novel Routes for the Production of bio-based Para-Xylene
  • 批准号:
    1434548
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $29.95万
  • 财政年份:
    2014
  • 负责人:
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  • 依托单位:
海外基金