• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于可识别性分析的双螺杆湿法制粒一维总体平衡模型的改进

Improvement of a 1D Population Balance Model for Twin-Screw Wet Granulation by Using Identifiability Analysis.

作者信息

Barrera Jiménez Ana Alejandra, Van Hauwermeiren Daan, Peeters Michiel, De Beer Thomas, Nopens Ingmar

机构信息

BIOMATH-Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure Links 653, 9000 Ghent, Belgium.

Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium.

出版信息

Pharmaceutics. 2021 May 11;13(5):692. doi: 10.3390/pharmaceutics13050692.

DOI:10.3390/pharmaceutics13050692
PMID:34064771
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8151179/
Abstract

Recently, the pharmaceutical industry has undergone changes in the production of solid oral dosages from traditional inefficient and expensive batch production to continuous manufacturing. The latest advancements include increased use of continuous twin-screw wet granulation and application of advanced modeling tools such as Population Balance Models (PBMs). However, improved understanding of the physical process within the granulator and improvement of current population balance models are necessary for the continuous production process to be successful in practice. In this study, an existing compartmental one-dimensional PBM of a twin-screw granulation process was improved by altering the original aggregation kernel in the wetting zone as a result of an identifiability analysis. In addition, a strategy was successfully applied to reduce the number of model parameters to be calibrated in both the wetting zone and kneading zones. It was found that the new aggregation kernel in the wetting zone is capable of reproducing the particle size distribution that is experimentally observed at different process conditions as well as different types of formulations, varying in hydrophilicity and API concentration. Finally, it was observed that model parameters could be linked not only to the material properties but also to the liquid to solid ratio, paving the way to create a generic PBM to predict the particle size distribution of a new formulation.

摘要

最近,制药行业在固体口服制剂生产方面经历了变革,从传统低效且昂贵的批次生产转向连续制造。最新进展包括更多地使用连续双螺杆湿法制粒以及应用先进的建模工具,如群体平衡模型(PBMs)。然而,要使连续生产过程在实践中取得成功,有必要更好地理解制粒机内部的物理过程并改进当前的群体平衡模型。在本研究中,通过可识别性分析改变了润湿区的原始聚集核,从而改进了现有的双螺杆制粒过程的一维隔室PBM。此外,成功应用了一种策略来减少在润湿区和捏合区中需要校准的模型参数数量。结果发现,润湿区的新聚集核能够重现不同工艺条件以及不同类型制剂(亲水性和原料药浓度各异)下实验观察到的粒度分布。最后,观察到模型参数不仅可以与材料特性相关联,还可以与液固比相关联,为创建通用PBM以预测新制剂的粒度分布铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/03339458a15f/pharmaceutics-13-00692-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/ea8b00a2f9ab/pharmaceutics-13-00692-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/80a2e748e377/pharmaceutics-13-00692-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/9d0c92b32dcb/pharmaceutics-13-00692-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/d26830811569/pharmaceutics-13-00692-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/9635c67dcb3f/pharmaceutics-13-00692-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/8cc77936973c/pharmaceutics-13-00692-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/bab8390d79c7/pharmaceutics-13-00692-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/88d7f862bc23/pharmaceutics-13-00692-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/d4c4c3532761/pharmaceutics-13-00692-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/4254b05e575b/pharmaceutics-13-00692-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/f11ce1142d64/pharmaceutics-13-00692-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/f28ab1fe4998/pharmaceutics-13-00692-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/a6663a0dbf68/pharmaceutics-13-00692-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/bdfb891b4494/pharmaceutics-13-00692-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/d6f0c8f4f578/pharmaceutics-13-00692-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/607b775f1ef0/pharmaceutics-13-00692-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/7187dbe86563/pharmaceutics-13-00692-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/a8c8ec43f088/pharmaceutics-13-00692-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/03339458a15f/pharmaceutics-13-00692-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/ea8b00a2f9ab/pharmaceutics-13-00692-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/80a2e748e377/pharmaceutics-13-00692-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/9d0c92b32dcb/pharmaceutics-13-00692-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/d26830811569/pharmaceutics-13-00692-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/9635c67dcb3f/pharmaceutics-13-00692-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/8cc77936973c/pharmaceutics-13-00692-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/bab8390d79c7/pharmaceutics-13-00692-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/88d7f862bc23/pharmaceutics-13-00692-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/d4c4c3532761/pharmaceutics-13-00692-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/4254b05e575b/pharmaceutics-13-00692-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/f11ce1142d64/pharmaceutics-13-00692-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/f28ab1fe4998/pharmaceutics-13-00692-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/a6663a0dbf68/pharmaceutics-13-00692-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/bdfb891b4494/pharmaceutics-13-00692-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/d6f0c8f4f578/pharmaceutics-13-00692-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/607b775f1ef0/pharmaceutics-13-00692-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/7187dbe86563/pharmaceutics-13-00692-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/a8c8ec43f088/pharmaceutics-13-00692-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8660/8151179/03339458a15f/pharmaceutics-13-00692-g019.jpg

相似文献

1
Improvement of a 1D Population Balance Model for Twin-Screw Wet Granulation by Using Identifiability Analysis.基于可识别性分析的双螺杆湿法制粒一维总体平衡模型的改进
Pharmaceutics. 2021 May 11;13(5):692. doi: 10.3390/pharmaceutics13050692.
2
Linking granulation performance with residence time and granulation liquid distributions in twin-screw granulation: An experimental investigation.双螺杆制粒中造粒性能与停留时间及造粒液分布的关联:一项实验研究
Eur J Pharm Sci. 2016 Jul 30;90:25-37. doi: 10.1016/j.ejps.2015.12.021. Epub 2015 Dec 18.
3
Multi-dimensional population balance modelling of pharmaceutical formulations for continuous twin-screw wet granulation: Determination of liquid distribution.多维度药物制剂连续双螺杆湿法造粒的颗粒群平衡模型建立:液体分布的测定。
Int J Pharm. 2019 Jul 20;566:352-360. doi: 10.1016/j.ijpharm.2019.06.001. Epub 2019 Jun 3.
4
In-depth experimental analysis of pharmaceutical twin-screw wet granulation in view of detailed process understanding.鉴于对详细工艺的理解,对药物双螺杆湿法制粒进行深入实验分析。
Int J Pharm. 2017 Aug 30;529(1-2):678-693. doi: 10.1016/j.ijpharm.2017.07.045. Epub 2017 Jul 15.
5
Partial least squares regression to calculate population balance model parameters from material properties in continuous twin-screw wet granulation.基于连续双螺杆湿法造粒中材料性能计算颗粒群平衡模型参数的偏最小二乘回归法。
Int J Pharm. 2023 Jun 10;640:123040. doi: 10.1016/j.ijpharm.2023.123040. Epub 2023 May 10.
6
In-line temperature measurement to improve the understanding of the wetting phase in twin-screw wet granulation and its use in process development.在线温度测量提高了对双螺杆湿法造粒中润湿相的理解及其在工艺开发中的应用。
Int J Pharm. 2020 Jun 30;584:119451. doi: 10.1016/j.ijpharm.2020.119451. Epub 2020 May 23.
7
Assessment of spatial heterogeneity in continuous twin screw wet granulation process using three-compartmental population balance model.使用三腔室颗粒种群平衡模型评估连续双螺杆湿法造粒过程中的空间异质性。
Pharm Dev Technol. 2019 Jan;24(1):105-117. doi: 10.1080/10837450.2018.1427106. Epub 2018 Jan 25.
8
Complete two dimensional population balance modelling of wet granulation in twin screw.在双螺杆中进行湿法造粒的二维完整颗粒平衡建模。
Int J Pharm. 2020 Dec 15;591:120018. doi: 10.1016/j.ijpharm.2020.120018. Epub 2020 Oct 26.
9
Compartmental approach for modelling twin-screw granulation using population balances.采用颗粒群平衡模型对双螺杆造粒进行分区建模。
Int J Pharm. 2020 Feb 25;576:118737. doi: 10.1016/j.ijpharm.2019.118737. Epub 2019 Nov 18.
10
Managing API raw material variability during continuous twin-screw wet granulation.在连续双螺杆湿法造粒过程中管理原料药 API 的变异性。
Int J Pharm. 2019 Apr 20;561:265-273. doi: 10.1016/j.ijpharm.2019.03.012. Epub 2019 Mar 6.

引用本文的文献

1
Pharmaceutical Application of Process Understanding and Optimization Techniques: A Review on the Continuous Twin-Screw Wet Granulation.过程理解与优化技术的制药应用:连续双螺杆湿法制粒综述
Biomedicines. 2023 Jul 6;11(7):1923. doi: 10.3390/biomedicines11071923.
2
Risk Assessment for a Twin-Screw Granulation Process Using a Supervised Physics-Constrained Auto-encoder and Support Vector Machine Framework.基于监督式物理约束自动编码器和支持向量机框架的双螺杆制粒工艺风险评估。
Pharm Res. 2022 Sep;39(9):2095-2107. doi: 10.1007/s11095-022-03313-y. Epub 2022 Aug 4.
3
Advances in Twin-Screw Granulation.

本文引用的文献

1
Characterization of Simultaneous Evolution of Size and Composition Distributions Using Generalized Aggregation Population Balance Equation.使用广义聚集种群平衡方程对尺寸和组成分布的同时演变进行表征
Pharmaceutics. 2020 Nov 27;12(12):1152. doi: 10.3390/pharmaceutics12121152.
2
Complete two dimensional population balance modelling of wet granulation in twin screw.在双螺杆中进行湿法造粒的二维完整颗粒平衡建模。
Int J Pharm. 2020 Dec 15;591:120018. doi: 10.1016/j.ijpharm.2020.120018. Epub 2020 Oct 26.
3
SciPy 1.0: fundamental algorithms for scientific computing in Python.
双螺杆制粒技术的进展
Pharmaceutics. 2021 Dec 27;14(1):46. doi: 10.3390/pharmaceutics14010046.
SciPy 1.0:Python 中的科学计算基础算法。
Nat Methods. 2020 Mar;17(3):261-272. doi: 10.1038/s41592-019-0686-2. Epub 2020 Feb 3.
4
Continuous twin screw granulation: Impact of binder addition method and surfactants on granulation of a high-dosed, poorly soluble API.连续双螺杆造粒:黏合剂添加方式和表面活性剂对高剂量难溶性 API 制粒的影响。
Int J Pharm. 2020 Mar 15;577:119068. doi: 10.1016/j.ijpharm.2020.119068. Epub 2020 Jan 22.
5
Continuous twin screw granulation: A complex interplay between formulation properties, process settings and screw design.连续双螺杆造粒:配方特性、工艺参数和螺杆设计之间的复杂相互作用。
Int J Pharm. 2020 Feb 25;576:119004. doi: 10.1016/j.ijpharm.2019.119004. Epub 2020 Jan 11.
6
Multi-dimensional population balance modelling of pharmaceutical formulations for continuous twin-screw wet granulation: Determination of liquid distribution.多维度药物制剂连续双螺杆湿法造粒的颗粒群平衡模型建立:液体分布的测定。
Int J Pharm. 2019 Jul 20;566:352-360. doi: 10.1016/j.ijpharm.2019.06.001. Epub 2019 Jun 3.
7
Twin Screw Granulation: An Investigation of the Effect of Barrel Fill Level.双螺杆制粒:料筒填充水平影响的研究
Pharmaceutics. 2018 Jun 1;10(2):67. doi: 10.3390/pharmaceutics10020067.
8
Assessment of spatial heterogeneity in continuous twin screw wet granulation process using three-compartmental population balance model.使用三腔室颗粒种群平衡模型评估连续双螺杆湿法造粒过程中的空间异质性。
Pharm Dev Technol. 2019 Jan;24(1):105-117. doi: 10.1080/10837450.2018.1427106. Epub 2018 Jan 25.
9
In-depth experimental analysis of pharmaceutical twin-screw wet granulation in view of detailed process understanding.鉴于对详细工艺的理解,对药物双螺杆湿法制粒进行深入实验分析。
Int J Pharm. 2017 Aug 30;529(1-2):678-693. doi: 10.1016/j.ijpharm.2017.07.045. Epub 2017 Jul 15.
10
Use of the channel fill level in defining a design space for twin screw wet granulation.在定义双螺杆湿法制粒的设计空间时通道填充水平的应用。
Int J Pharm. 2017 Mar 15;519(1-2):165-177. doi: 10.1016/j.ijpharm.2017.01.029. Epub 2017 Jan 15.