PFI-RP: Sensors, Computational Modeling, and Bioanalytical Technologies for Closed-Loop Lyophilization
PFI-RP: Sensors, Computational Modeling, and Bioanalytical Technologies for Closed-Loop Lyophilization
批准号:
1827717
负责人:
Alina Alexeenko
金额:
$75.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-15 至 2022-08-31
中文摘要
该PFI项目更广泛的影响/商业潜力在于提供实时传感器技术、计算建模和生物分析工具,以加速冻干药物的生产,从而实现更具成本效益的救生药物生产。自2008年以来,超过40%的FDA批准的生物药物以冻干剂型上市,许多药物产品在没有冻干的情况下无法商业化。然而,冻干是制药生产中最昂贵和耗时的单元操作之一,具有分批模式操作、开环处理和缺乏实时产品质量监测。典型的生产冻干周期通常需要几天到两周,典型的运营成本超过每天50,000美元。由于缺乏过程中产品监测和闭环控制,过度保守的循环导致多达30%的时间被浪费。该项目将把目前正在开发的几种技术转化为生产准备,并将加速向自动冻干的过渡,实现“自动驾驶”冻干机。拟议的项目通过共同开发解决三个相互关联的技术挑战:㈠使用符合无菌处理要求的无线探头进行无创产品温度监测; ㈡通过固态氢氘交换质谱法进行加速生物分子稳定性分析;和(iii)实时冻干速率测量和封闭-基于分布式无线探头的回路过程控制以及产品、容器和冻干机设备中的传热和传质的计算建模。预计项目活动将增进若干领域的知识,即a)低压条件下的流体/热传输; B)极端环境下射频系统的柔性混合电子器件; c)生物分子降解机制和分析方法。这些技术将在普渡大学的冻干技术示范设施的冻干机中实施,并与行业合作伙伴合作,在现实的制造限制条件下进行测试。研究和技术开发活动将通过向冻干用户群体传播结果来补充。与该计划中开发的技术相关的教育模块将包括在由普渡大学的工业大学联盟LyoHUB组织的培训课程中。此外,通过与Purdue Foundry的合作,该团队将教育学生将工程和制药技术发明商业化。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The broader impact/commercial potential of this PFI project is in providing real-time sensor technologies, computational modeling and bioanalytical tools for accelerated manufacturing of lyophilized pharmaceuticals that will enable more cost-efficient manufacturing of life-saving medicines. Over 40% of the biopharmaceuticals approved by FDA since 2008 are marketed in lyophilized dosage forms, and many pharmaceutical products could not be commercially viable without lyophilization. However, lyophilization is among the most expensive and time-consuming unit operations in pharmaceutical manufacturing, with batch-mode operation, open-loop processing, and lack of real-time product quality monitoring. A typical production lyophilization cycle usually takes from a few days to two weeks with typical operating costs of over $50,000 per day. As much as 30% of this time is wasted because of overly conservative cycles due to lack of in-process product monitoring and closed-loop control. This project will translate to manufacturing readiness several technologies that are currently in development and will accelerate the transition to automated lyophilization and enable "self-driving" lyophilizers. The proposed project addresses three interconnected technical challenges by co-development of: (i) Noninvasive product temperature monitoring using wireless probes that are compatible with aseptic processing requirements; (ii) Accelerated biomolecule stability analytics by solid-state hydrogen-deuterium exchange mass spectrometry; and (iii) Real-time lyophilization rate measurement and closed-loop process control based on distributed wireless probes and computational modeling of the heat and mass transfer in the product, container and the lyophilizer equipment. The project activities are expected to advance knowledge in several fields, namely a) fluid/thermal transport in low-pressure conditions; b) flexible hybrid electronics for RF systems in extreme environments; c) biomolecule degradation mechanisms and analytical methods. The technologies will be implemented in a lyophilizer at Purdue's lyophilization technology demonstration facility and tested under realistic manufacturing constraints in collaboration with industry partners. The research and technology development activities will be complemented by dissemination of results to the lyophilization user community. Educational modules related to technologies developed in this program will be included in training courses organized by LyoHUB, an industry-university consortium based at Purdue University. Additionally, by cooperating with Purdue Foundry, the team will educate students in commercialization for engineering and pharmaceutical technology inventions.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.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
LyoPRONTO: an Open-Source Lyophilization Process Optimization Tool
LyoPRONTO:开源冻干工艺优化工具
DOI:
10.1208/s12249-019-1532-7
发表时间:
2019
期刊:
AAPS PharmSciTech
影响因子:
3.3
作者:
[Shivkumar, Gayathri, Kazarin, Petr S., Strongrich, Andrew D., Alexeenko, Alina A.]
通讯作者:
Alexeenko, Alina A.
Effects of temperature and relative humidity in D2O on solid-state hydrogen deuterium exchange mass spectrometry (ssHDX-MS)
D2O 中的温度和相对湿度对固态氢氘交换质谱 (ssHDX-MS) 的影响
DOI:
10.1016/j.ijpharm.2021.120263
发表时间:
2021
期刊:
International Journal of Pharmaceutics
影响因子:
5.8
作者:
[Tukra, Rishabh, Gardner, Sam, Topp, Elizabeth M.]
通讯作者:
Topp, Elizabeth M.
DOI:
10.1016/j.ejpb.2021.09.005
发表时间:
2021-09-24
期刊:
EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS
影响因子:
4.9
作者:
[Strongrich, Andrew, Alexeenko, Alina]
通讯作者:
Alexeenko, Alina
Collaborative Research: CubeSat Ideas Lab: VIrtual Super-resolution Optics with Reconfigurable Swarms (VISORS)
-
批准号:1936531
-
项目类别:Continuing Grant
-
资助金额:$12.71万
-
财政年份:2019
-
负责人:Alina Alexeenko
-
依托单位:
CDS&E: DEterministic Evaluation of Kinetic Boltzmann equation with Spectral H/p/v Accuracy (DEEKSHA)
-
批准号:1854829
-
项目类别:Standard Grant
-
资助金额:$33.12万
-
财政年份:2019
-
负责人:Alina Alexeenko
-
依托单位:
PFI:AIR-TT: Microscale Gas Sensor for Process Monitoring and Control in Bio/Pharmaceutical Lyophilization
-
批准号:1602061
-
项目类别:Standard Grant
-
资助金额:$20.0万
-
财政年份:2016
-
负责人:Alina Alexeenko
-
依托单位:
CAREER: Quantifying and Exploiting Knudsen Thermal Forces in Nano/Microsystems
-
批准号:1055453
-
项目类别:Standard Grant
-
资助金额:$40.0万
-
财政年份:2011
-
负责人:Alina Alexeenko
-
依托单位:
GOALI: Modeling and Control of Fluid Dynamics and Ice Formation in Pharmaceutical Freeze-Drying
-
批准号:0829047
-
项目类别:Standard Grant
-
资助金额:$9.32万
-
财政年份:2008
-
负责人:Alina Alexeenko
-
依托单位:
国内基金
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