FMRG: Eco: Cyber Enabled Transformation to Circular Supply Chains for Sustainable Pharmaceutical Manufacturing Networks
FMRG:Eco:通过网络实现循环供应链转型,实现可持续药品制造网络
基本信息
- 批准号:2229250
- 负责人:
- 金额:$ 300万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-11-01 至 2026-10-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Current pharmaceutical manufacturing systems follow the linear model of “take, make, and dispose”. This model is neither economically nor environmentally sustainable. To enable future manufacturing to transition to a circular economy, making more efficient use of materials through recycling and repurposing, there is a growing emphasis on moving towards circular supply chains (CSCs). Many industries have begun to convert from centralized batch manufacturing to automation-driven continuous manufacturing that is based on actual, rather than predicted, levels of demand. Yet, while this reduces waste at the single-plant scale, it is not sufficient for the creation of a complete zero waste CSC integrated industrial ecosystem. Models do not exist that connect single-scale plants to the larger network, making it impossible to account for feedback interactions between single-scale process innovations and existing processes across the manufacturing network to optimize resource utilization. The goal of this project is to enable the design of zero waste future pharmaceutical manufacturing networks at a macroscale using an integrative, multidisciplinary approach focused on novel process chemistry and separation methods, macroscale modeling of manufacturing networks to integrate new processes at scale, and pricing optimization for collaborative decision making through dedicated cyberinfrastructure development. The cyberinfrastructure developed will aid in understanding the feedback loops between plant-scale automated manufacturing and macroscale manufacturing networks in making optimal decisions for adoption of recycling processes at scale and redesign of material flows towards CSCs. Targeted key contributions of the project are: 1) creating novel modular recycling processes for waste medicines to enable CSCs and digital twin models for the facilities, 2) automating the integration of novel processes in an existing network by advancing algorithms for multi- scale integration and advancing cyberinfrastructure, and 3) creating a dual pricing mechanism and econometric model to transition the whole system to a CSC by facilitating waste exchange and use of recycled active ingredients. These advancements will provide a framework to drive innovations in manufacturing processes at the single scale in convergence with macroscale manufacturing networks to create a zero-waste future manufacturing system. The approach of integrating modular manufacturing processes at the right scale in the overall network for zero waste pharmaceutical manufacturing will be generalizable to other future manufacturing networks. Graduate education in engineering will be enhanced to include convergence thinking by developing a “Computational Lab” to train interdisciplinary students in process design through macroscale network interactions for economic and environmental sustainability. Undergraduates and minority students will be engaged in research through Purdue's SURF program and existing Purdue partnerships with HBCUs and Purdue’s Women in Engineering program. For future workforce development in pharmaceutical manufacturing, the project team will partner with Purdue’s existing Biotechnology Innovation and Regulatory Science program and Office of Professional Practice to translate the research outcomes into industrial practice training through workshops for industrial stakeholders, student internships, and partnerships with Ivy Tech Community College. Integration through a web-based Hub of citizen data for use in driving network decisions will facilitate participation of citizens in sustainable future manufacturing.This Future Manufacturing award is supported by the following NSF divisions/directorates: CBET/ENG, CMMI/ENG, CHE/MPS, and SBE.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.
目前的药品生产系统遵循“取、造、弃”的线性模型。这种模式在经济上和环境上都是不可持续的。为了使未来的制造业能够过渡到循环经济,通过回收和再利用来更有效地利用材料,人们越来越重视转向循环供应链(CSC)。许多行业已经开始从集中式批量制造转变为自动化驱动的连续制造,这种制造基于实际的需求水平,而不是预测的水平。然而,尽管这减少了单厂规模的废物,但这还不足以创建一个完整的零废物CSC综合工业生态系统。不存在将单一规模的工厂连接到更大网络的模型,因此无法考虑单一规模的工艺创新与整个制造网络中现有工艺之间的反馈交互作用,以优化资源利用。该项目的目标是使用专注于新的过程化学和分离方法的综合、多学科方法在宏观范围内设计零废物的未来制药制造网络,对制造网络进行宏观建模以在规模上整合新过程,并通过专门的网络基础设施开发实现价格优化以进行协作决策。开发的网络基础设施将有助于了解工厂规模的自动化制造和大规模制造网络之间的反馈回路,从而为大规模采用回收工艺和重新设计流向CSC的材料流做出最佳决策。该项目的主要目标是:1)为废旧药品创建新的模块化回收流程,以支持CSC和设施的数字孪生模式;2)通过改进多尺度整合的算法和推进网络基础设施,使现有网络中的新流程整合自动化;3)创建双重定价机制和计量模型,通过促进废物交换和使用回收的活性成分,将整个系统过渡到CSC。这些进步将提供一个框架,以推动单一规模的制造工艺创新,与宏观制造网络融合,创建一个零浪费的未来制造系统。这种在整体网络中集成适当规模的模块化制造过程以实现零废物药品制造的方法将可推广到其他未来的制造网络。工程方面的研究生教育将得到加强,通过开发一个“计算实验室”,通过宏观网络互动为经济和环境可持续性培训跨学科学生进行过程设计方面的融合思维。本科生和少数族裔学生将通过普渡大学的SURF计划以及普渡大学与HBCU和普渡大学工程女性计划的现有合作伙伴关系从事研究。对于制药制造领域未来的劳动力发展,项目团队将与普渡大学现有的生物技术创新与监管科学计划和专业实践办公室合作,通过为行业利益相关者举办研讨会、学生实习以及与常春藤科技社区学院的合作伙伴关系,将研究成果转化为工业实践培训。通过用于推动网络决策的基于网络的公民数据中心的整合,将促进公民参与可持续的未来制造。该未来制造奖由以下NSF部门/理事会支持:CBET/ENG、CMMI/ENG、CHE/MPS和SBE。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,认为值得支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A hybrid mechanistic machine learning approach to model industrial network dynamics for sustainable design of emerging carbon capture and utilization technologies
一种混合机械机器学习方法,用于模拟工业网络动态,以实现新兴碳捕获和利用技术的可持续设计
- DOI:10.1039/d3se01032e
- 发表时间:2023
- 期刊:
- 影响因子:5.6
- 作者:Shekhar, Abhimanyu Raj;Moar, Raghav R.;Singh, Shweta
- 通讯作者:Singh, Shweta
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Shweta Singh其他文献
Monitoring potential molecular interactions of adenine with other amino acids using Raman spectroscopy and DFT modeling.
使用拉曼光谱和 DFT 建模监测腺嘌呤与其他氨基酸的潜在分子相互作用。
- DOI:
10.1016/j.saa.2015.04.066 - 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Shweta Singh;P. Donfack;S. Srivastava;D. Singh;A. Materny;B. P. Asthana;P. C. Mishra - 通讯作者:
P. C. Mishra
Capturing Human Gestures for Sign Language Detection: An Advance Technique for Detection to Help Deprived Section of Society
捕捉人类手势进行手语检测:一种先进的检测技术来帮助社会贫困阶层
- DOI:
10.1109/icacctech61146.2023.00124 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Medha Malik;Malvika Gupta;Shweta Singh;Payal Malik - 通讯作者:
Payal Malik
Pharmacokinetic Analysis of Ursolic Acid in Alstonia scholaris R. Br. by High-Performance Thin-Layer Chromatography
熊果酸的药代动力学分析
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:1.6
- 作者:
P. Shetty;K. Mangaonkar;R. Sane;K. K. Jaripatke;Shweta Singh - 通讯作者:
Shweta Singh
Phenotype variations in Lafora progressive myoclonus epilepsy: possible involvement of genetic modifiers?
Lafora 进行性肌阵挛癫痫的表型变异:可能涉及遗传修饰剂?
- DOI:
10.1038/jhg.2012.29 - 发表时间:
2012 - 期刊:
- 影响因子:3.5
- 作者:
Shweta Singh;S. Ganesh - 通讯作者:
S. Ganesh
Synthesis, structural studies, and antimicrobial activity of polymeric copper(II) tetrathiocyanato diargentate(I) complexes with some acylhydrazones
聚合四硫氰酸铜(II)二银酸铜(I)与某些酰腙配合物的合成、结构研究和抗菌活性
- DOI:
10.1002/app.28565 - 发表时间:
2008 - 期刊:
- 影响因子:0
- 作者:
V. Singh;Archana Singh;Shweta Singh - 通讯作者:
Shweta Singh
Shweta Singh的其他文献
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{{ truncateString('Shweta Singh', 18)}}的其他基金
Collaborative Research: MRA: Scale, Space, and Time: A Unifying Approach to Aquatic Invasions
合作研究:MRA:规模、空间和时间:水生入侵的统一方法
- 批准号:
2017858 - 财政年份:2021
- 资助金额:
$ 300万 - 项目类别:
Standard Grant
Process Engineering Models to Physical Input-Output Tables (PIOTs): A Novel Approach to Reproducible, Transparent and Fast Regional PIOT Development Via Collaborative PIOTHub
物理输入输出表 (PIOT) 的过程工程模型:通过协作 PIOTHub 实现可重复、透明和快速的区域 PIOT 开发的新方法
- 批准号:
1805741 - 财政年份:2018
- 资助金额:
$ 300万 - 项目类别:
Standard Grant
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