The Move toward Biopharma 4.0

Abstract

Genetic Engineering & Biotechnology NewsVol. 39, No. 6 Bioprocessing TutorialThe Move toward Biopharma 4.0Insilico Biotechnology develops “smart” processes that benefit biomanufacturing through Digital TwinsShilpa Nargund, PhD, Kathrin Guenther, PhD, and Klaus MauchShilpa Nargund, PhDShilpa Nargund, PhD, is a Data Scientist & Business Development ManagerSearch for more papers by this author, Kathrin Guenther, PhDKathrin Guenther, PhD, is a Sr. Business Development ManagerSearch for more papers by this author, and Klaus MauchKlaus Mauch E-mail Address: (klaus.mauch@insilico-biotechnology.com) is the CEO & CTO at Insilico Biotechnology. Website: www.insilico-biotechnology.comSearch for more papers by this authorPublished Online:29 May 2019https://doi.org/10.1089/gen.39.06.18AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetailsCited byContinuous integrated manufacturing for biopharmaceuticals: A new paradigm or an empty promise?28 September 2022 | Biotechnology and Bioengineering, Vol. 120, No. 2Exploring the potential of machine learning for more efficient development and production of biopharmaceuticals11 August 2022 | Biotechnology Progress, Vol. 38, No. 6Arduino Soft Sensor for Monitoring Schizochytrium sp. Fermentation, a Proof of Concept for the Industrial Application of Genome-Scale Metabolic Models in the Context of Pharma 4.029 October 2022 | Processes, Vol. 10, No. 11Architectural and Technological Improvements to Integrated Bioprocess Models towards Real-Time Applications9 October 2022 | Bioengineering, Vol. 9, No. 10Artificial intelligence and machine learning applications in biopharmaceutical manufacturingTrends in Biotechnology, Vol. 349AI-ML applications in bioprocessing: ML as an enabler of real time quality prediction in continuous manufacturing of mAbsComputers & Chemical Engineering, Vol. 164Holistic Process Models: A Bayesian Predictive Ensemble Method for Single and Coupled Unit Operation Models29 March 2022 | Processes, Vol. 10, No. 4Modeling and optimization of bioreactor processesReprint of: Basic considerations for a digital twin of biointelligent systems: Applying technical design patterns to biological systemsCIRP Journal of Manufacturing Science and Technology, Vol. 34Computational Efforts for the Development and Scale-up of Antibody-Producing Cell Culture Processes1 January 2022Continuous downstream bioprocessing for intensified manufacture of biopharmaceuticals and antibodiesChemical Engineering ScienceBasic considerations for a digital twin of biointelligent systems: Applying technical design patterns to biological systemsCIRP Journal of Manufacturing Science and Technology, Vol. 31Digitalization in microbiology – Paving the path to sustainable circular bioeconomyNew Biotechnology, Vol. 59ChromaTech: A discontinuous Galerkin spectral element simulator for preparative liquid chromatographyComputers & Chemical Engineering, Vol. 141Digital Twins and Their Role in Model-Assisted Design of Experiments15 August 2020The Kalman Filter for the Supervision of Cultivation Processes11 November 2020History and Evolution of Modeling in Biotechnology: Modeling & Simulation, Application and Hardware PerformanceComputational and Structural Biotechnology Journal, Vol. 18The Rocky Road From Fed-Batch to Continuous Processing With E. coli20 November 2019 | Frontiers in Bioengineering and Biotechnology, Vol. 7 Volume 39Issue 6Jun 2019 InformationCopyright © by GEN PublishingTo cite this article:Shilpa Nargund, PhD, Kathrin Guenther, PhD, and Klaus Mauch.The Move toward Biopharma 4.0.Genetic Engineering & Biotechnology News.Jun 2019.53-55.http://doi.org/10.1089/gen.39.06.18Published in Volume: 39 Issue 6: May 29, 2019PDF download