{"title":"进料间歇生物反应器建模","authors":"Tilen Gimpelj , Aleksandar Tošić","doi":"10.1016/j.softx.2025.102358","DOIUrl":null,"url":null,"abstract":"<div><div>This paper describes an open-source computational tool developed for the modeling and simulation of fed-batch bioreactors, particularly for processes employing Chinese Hamster Ovary (CHO) cells, which are integral to biopharmaceutical manufacturing. The software provides a platform for researchers and industry professionals to simulate bioreactor dynamics and investigate the impact of various operational parameters, such as nutrient supply rates, oxygen concentrations, and temperature, prior to physical experimentation. The tool enables users to generate predictions of critical variables including cell density, nutrient consumption, and product concentration profiles over time. These predictions are derived from a mathematical framework based on a system of ordinary differential equations solved using the Runge–Kutta method. A notable capability of the software is the import of experimental data and the application of the Nelder–Mead algorithm for parameter optimization, allowing for the calibration of the model against empirical findings, thereby enhancing its predictive accuracy. The software supports in silico experimentation, which can contribute to reducing the time, cost, and resources associated with optimizing bioreactor configurations and scaling up production processes. By providing a refined and adaptable framework, this instrument assists in improving the understanding of bioreactor dynamics, optimizing biopharmaceutical production methodologies, and correlating theoretical models with practical bioreactor operations. The software is available as an open-source project to promote its adoption and continued development within the scientific community.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"32 ","pages":"Article 102358"},"PeriodicalIF":2.4000,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fed-batch bioreactor modeling\",\"authors\":\"Tilen Gimpelj , Aleksandar Tošić\",\"doi\":\"10.1016/j.softx.2025.102358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper describes an open-source computational tool developed for the modeling and simulation of fed-batch bioreactors, particularly for processes employing Chinese Hamster Ovary (CHO) cells, which are integral to biopharmaceutical manufacturing. The software provides a platform for researchers and industry professionals to simulate bioreactor dynamics and investigate the impact of various operational parameters, such as nutrient supply rates, oxygen concentrations, and temperature, prior to physical experimentation. The tool enables users to generate predictions of critical variables including cell density, nutrient consumption, and product concentration profiles over time. These predictions are derived from a mathematical framework based on a system of ordinary differential equations solved using the Runge–Kutta method. A notable capability of the software is the import of experimental data and the application of the Nelder–Mead algorithm for parameter optimization, allowing for the calibration of the model against empirical findings, thereby enhancing its predictive accuracy. The software supports in silico experimentation, which can contribute to reducing the time, cost, and resources associated with optimizing bioreactor configurations and scaling up production processes. By providing a refined and adaptable framework, this instrument assists in improving the understanding of bioreactor dynamics, optimizing biopharmaceutical production methodologies, and correlating theoretical models with practical bioreactor operations. The software is available as an open-source project to promote its adoption and continued development within the scientific community.</div></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":\"32 \",\"pages\":\"Article 102358\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352711025003243\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711025003243","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
This paper describes an open-source computational tool developed for the modeling and simulation of fed-batch bioreactors, particularly for processes employing Chinese Hamster Ovary (CHO) cells, which are integral to biopharmaceutical manufacturing. The software provides a platform for researchers and industry professionals to simulate bioreactor dynamics and investigate the impact of various operational parameters, such as nutrient supply rates, oxygen concentrations, and temperature, prior to physical experimentation. The tool enables users to generate predictions of critical variables including cell density, nutrient consumption, and product concentration profiles over time. These predictions are derived from a mathematical framework based on a system of ordinary differential equations solved using the Runge–Kutta method. A notable capability of the software is the import of experimental data and the application of the Nelder–Mead algorithm for parameter optimization, allowing for the calibration of the model against empirical findings, thereby enhancing its predictive accuracy. The software supports in silico experimentation, which can contribute to reducing the time, cost, and resources associated with optimizing bioreactor configurations and scaling up production processes. By providing a refined and adaptable framework, this instrument assists in improving the understanding of bioreactor dynamics, optimizing biopharmaceutical production methodologies, and correlating theoretical models with practical bioreactor operations. The software is available as an open-source project to promote its adoption and continued development within the scientific community.
期刊介绍:
SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.