Microbial technologies for biotherapeutics production: Key tools for advanced biopharmaceutical process development and control

Drug Discovery Today: Technologies - Tập 38 - Trang 9-24 - 2020
Denes Zalai1, Julian Kopp2, Bence Kozma2, Michael Küchler1, Christoph Herwig2,3, Julian Kager2
1Richter-Helm BioLogics GmbH & Co. KG, Suhrenkamp 59, 22335 Hamburg, Germany
2Research Division Biochemical Engineering, Institute of Chemical Environmental and Bioscience Engineering, Vienna University of Technology, Vienna, Austria
3Competence Center CHASE GmbH, Altenbergerstraße 69, 4040 Linz, Austria

Tài liệu tham khảo

Junker, 2006, Bioprocess monitoring and computer control: key roots of the current PAT initiative, Biotechnol Bioeng, 95, 226, 10.1002/bit.21087 Schugerl, 2001, Progress in monitoring, modeling and control of bioprocesses during the last 20 years, J Biotechnol, 85, 149, 10.1016/S0168-1656(00)00361-8 Walsh, 2013 Bluff or Serious Biosimilar Bet? Med Mak n.d. http://www.themedicinemaker.com/business-regulation/bluff-or-serious-biosimilar-bet [accessed 14 June 2020]. Inc RAR BioPlan Associates. Manufacturing Costs Will Be Critical to Biosimilars’ Success. Pharma Manuf n.d. http://www.pharmamanufacturing.com/articles/2016/manufacturing-costs-will-be-critical-to-biosimilars-success/ [accessed 14 June 2020]. Ten years on: measuring the return from pharmaceutical innovation 2019 | Deloitte UK n.d. http://www2.deloitte.com/uk/en/pages/life-sciences-and-healthcare/articles/measuring-return-from-pharmaceutical-innovation.html [accessed 14 June 2020]. Sinclair, 2010, Delivering affordable biologics from gene to vial, BioProcess Int, 4 What does – and does not – drive. Biopharma Cost Performance n.d. http://www.bcg.com/publications/2017/biopharmaceuticals-operations-what-does-and-does-not-drive-biopharma-cost-performance.aspx [accessed 14 June 2020]. Lara, 2012, Plasmid DNA production for therapeutic applications, Methods Mol Biol Clifton NJ, 824, 271, 10.1007/978-1-61779-433-9_14 Zhang, 2019, Advances in mRNA vaccines for infectious diseases, Front Immunol, 10 Kormann, 2011, Expression of therapeutic proteins after delivery of chemically modified mRNA in mice, Nat Biotechnol, 29, 154, 10.1038/nbt.1733 Mantle, 2019, Cyberbiosecurity for biopharmaceutical products, Front Bioeng Biotechnol, 7, 10.3389/fbioe.2019.00116 Alldread, 2015, Biopharmaceutical factory of the future, Pharm Bioprocess, 3, 293, 10.4155/pbp.15.11 Gupta, 2017, Microbial platform technology for recombinant antibody fragment production: a review, Crit Rev Microbiol, 43, 31, 10.3109/1040841X.2016.1150959 Selas Castiñeiras, 2018, E. coli strain engineering for the production of advanced biopharmaceutical products, FEMS Microbiol Lett, 365, 10.1093/femsle/fny162 Sanchez-Garcia, 2016, Recombinant pharmaceuticals from microbial cells: a 2015 update, Microb Cell Factories, 15, 33, 10.1186/s12934-016-0437-3 Almquist, 2014, Kinetic models in industrial biotechnology – improving cell factory performance, Metab Eng, 24, 38, 10.1016/j.ymben.2014.03.007 Zahel, 2017, Integrated process modelling – a process validation life cycle companion, Bioeng Basel Switz, 4 ICH F, 2009 ICH F, 2006 Kiss, 2015, A systems engineering perspective on process integration in industrial biotechnology: process integration in industrial biotechnology, J Chem Technol Biotechnol, 90, 349, 10.1002/jctb.4584 ICH guidance for industry Q10 on pharmaceutical quality system 2008 Rathore, 2017, Role of knowledge management in development and lifecycle management of biopharmaceuticals, Pharm Res, 34, 243, 10.1007/s11095-016-2043-9 Mears, 2017, Mechanistic fermentation models for process design, monitoring, and control, Trends Biotechnol, 35, 914, 10.1016/j.tibtech.2017.07.002 Sinner, 2020, 1 Kritzinger, 2018, Digital Twin in manufacturing: a categorical literature review and classification, IFAC-Pap, 51, 1016 Lemmerer, 2019, Decoupling of recombinant protein production from Escherichia coli cell growth enhances functional expression of plant Leloir glycosyltransferases, Biotechnol Bioeng, 116, 1259, 10.1002/bit.26934 Rosano, 2019, New tools for recombinant protein production in Escherichia coli: a 5-year update, Protein Sci, 28, 1412, 10.1002/pro.3668 Ghanem, 2013, Current trends in separation of plasmid DNA vaccines: a review, Anal Chim Acta, 760, 1, 10.1016/j.aca.2012.11.006 Berlec, 2013, Current state and recent advances in biopharmaceutical production in Escherichia coli, yeasts and mammalian cells, J Ind Microbiol Biotechnol, 40, 257, 10.1007/s10295-013-1235-0 Spadiut, 2013, Microbials for the production of monoclonal antibodies and antibody fragments, Trends Biotechnol, 32, 54, 10.1016/j.tibtech.2013.10.002 Humer, 2019, Improving the performance of horseradish peroxidase by site-directed mutagenesis, Int J Mol Sci, 20, 10.3390/ijms20040916 Karyolaimos, 2019, Enhancing recombinant protein yields in the E. coli periplasm by combining signal peptide and production rate screening, Front Microbiol, 10, 1511, 10.3389/fmicb.2019.01511 Hausjell, 2020, The effects of lactose induction on a plasmid-free E. coli T7 expression system, Bioeng Basel Switz, 7 Kasli, 2019, Use of a design of experiments approach to optimise production of a recombinant antibody fragment in the periplasm of Escherichia coli: selection of signal peptide and optimal growth conditions, AMB Express, 9, 5, 10.1186/s13568-018-0727-8 Slouka, 2019, Perspectives of inclusion bodies for bio-based products: curse or blessing?, Appl Microbiol Biotechnol, 103, 1143, 10.1007/s00253-018-9569-1 Rinas, 2017, Bacterial inclusion bodies: discovering their better half, Trends Biochem Sci, 42, 726, 10.1016/j.tibs.2017.01.005 Humer, 2018, Wanted: more monitoring and control during inclusion body processing, World J Microbiol Biotechnol, 34, 158, 10.1007/s11274-018-2541-5 Kopp, 2019, The rocky road from fed-batch to continuous processing with E. coli, Front Bioeng Biotechnol, 7, 328, 10.3389/fbioe.2019.00328 de Groot, 2006, Effect of temperature on protein quality in bacterial inclusion bodies, FEBS Lett, 580, 6471, 10.1016/j.febslet.2006.10.071 Wunderlich, 2014, Effect of growth rate on plasmid DNA production and metabolic performance of engineered Escherichia coli strains, J Biosci Bioeng, 117, 336, 10.1016/j.jbiosc.2013.08.007 Freyre, 2000, Very high expression of an anti-carcinoembryonic antigen single chain Fv antibody fragment in the yeast Pichia pastoris, J Biotechnol, 76, 157, 10.1016/S0168-1656(99)00183-2 Spadiut, 2014, Quantitative comparison of dynamic physiological feeding profiles for recombinant protein production with Pichia pastoris, Bioprocess Biosyst Eng, 37, 1163, 10.1007/s00449-013-1087-z Damasceno, 2004, An optimized fermentation process for high-level production of a single-chain Fv antibody fragment in Pichia pastoris, Protein Expr Purif, 37, 18, 10.1016/j.pep.2004.03.019 Rodríguez Jiménez, 1997, Different methanol feeding strategies to recombinant Pichia pastoris cultures producing high level of dextranase, Biotechnol Tech, 11, 461, 10.1023/A:1018493428584 Spadiut, 2014, Determination of a dynamic feeding strategy for recombinant Pichia pastoris strains, Methods Mol Biol Clifton NJ, 1152, 185, 10.1007/978-1-4939-0563-8_11 Dietzsch, 2011, A dynamic method based on the specific substrate uptake rate to set up a feeding strategy for Pichia pastoris, Microb Cell Fact, 10, 14, 10.1186/1475-2859-10-14 Slouka, 2019, Monitoring and control strategies for inclusion body production in E. coli based on glycerol consumption, J Biotechnol, 296, 75, 10.1016/j.jbiotec.2019.03.014 Slouka, 2018, Custom made inclusion bodies: impact of classical process parameters and physiological parameters on inclusion body quality attributes, Microb Cell Factories, 17, 148, 10.1186/s12934-018-0997-5 Kopp, 2018, Inclusion body bead size in E. coli controlled by physiological feeding, Microorganisms, 6, 10.3390/microorganisms6040116 Wurm, 2017, Teaching an old pET new tricks: tuning of inclusion body formation and properties by a mixed feed system in E. coli, Appl Microbiol Biotechnol Jevsevar, 2005, Production of nonclassical inclusion bodies from which correctly folded protein can be extracted, Biotechnol Prog, 21, 632, 10.1021/bp0497839 Kloss, 2018, Catalytically active inclusion bodies of L-lysine decarboxylase from E. coli for 1,5-diaminopentane production, Sci Rep, 8, 5856, 10.1038/s41598-018-24070-2 Diener, 2016, Fusion of a coiled-coil domain facilitates the high-level production of catalytically active enzyme inclusion bodies, ChemCatChem, 8, 142, 10.1002/cctc.201501001 Chen, 1997, Automated fed-batch fermentation with feed-back controls based on dissolved oxygen (DO) and pH for production of DNA vaccines, J Ind Microbiol Biotechnol, 18, 43, 10.1038/sj.jim.2900355 Lee, 1996, High cell-density culture of Escherichia coli, Trends Biotechnol, 14, 98, 10.1016/0167-7799(96)80930-9 Henson, 2006, Biochemical reactor modeling and control, IEEE Control Syst Mag, 26, 54, 10.1109/MCS.2006.1657876 Peebo, 2018, Application of continuous culture methods to recombinant protein production in microorganisms, Microorganisms, 6, 10.3390/microorganisms6030056 Marschall, 2016, Tunable recombinant protein expression in E. coli: enabler for continuous processing?, Appl Microbiol Biotechnol, 100, 5719, 10.1007/s00253-016-7550-4 Schuller, 2020, Adaptive evolution in producing microtiter cultivations generates genetically stable Escherichia coli production hosts for continuous bioprocessing, Biotechnol J Kopp, 2019, Boosting recombinant inclusion body production – from classical fed-batch approach to continuous cultivation, Front Bioeng Biotechnol, 7, 10.3389/fbioe.2019.00297 Bioreaction engineering – modeling and control | K. Schügerl | Springer n.d. http://www.springer.com/de/book/9783642641039 [accessed 9 February 2021]. Balasundaram, 2009, Advances in product release strategies and impact on bioprocess design, Trends Biotechnol, 27, 477, 10.1016/j.tibtech.2009.04.004 Jungbauer, 2013, Continuous downstream processing of biopharmaceuticals, Trends Biotechnol, 31, 479, 10.1016/j.tibtech.2013.05.011 Barazzone, 2011, Production and purification of recombinant fragment of pneumococcal surface protein A (PspA) in Escherichia coli, Procedia in Vaccinology, 4, 27, 10.1016/j.provac.2011.07.005 Palmer, 2012, Preparation and extraction of insoluble (inclusion-body) proteins from Escherichia coli, Curr Protoc Protein Sci, 10.1002/0471140864.ps0603s70 Chatel, 2014, Ultra scale-down characterization of the impact of conditioning methods for harvested cell broths on clarification by continuous centrifugation-Recovery of domain antibodies from rec E. coli, Biotechnol Bioeng, 111, 913, 10.1002/bit.25164 Singh, 2005, Solubilization and refolding of bacterial inclusion body proteins, J Biosci Bioeng, 99, 303, 10.1263/jbb.99.303 Singh, 2015, Protein recovery from inclusion bodies of Escherichia coli using mild solubilization process, Microb Cell Factories, 14, 41, 10.1186/s12934-015-0222-8 Jungbauer, 2007, Current status of technical protein refolding, J Biotechnol, 128, 587, 10.1016/j.jbiotec.2006.12.004 Alibolandi, 2011, Chemical assistance in refolding of bacterial inclusion bodies, Biochem Res Int, 1, 10.1155/2011/631607 Kiefuaber, 1991, PRCmiN aggregation in vitro and in vivo: a quantitative model of the kinetic competition between folding and aggregation, Biotechnology, 5 Eiberle, 2010, Technical refolding of proteins: do we have freedom to operate?, Biotechnol J, 5, 547, 10.1002/biot.201000001 Zhang, 2009, Modeling of protein refolding from inclusion bodies, Acta Biochim Biophys Sin, 41, 1044, 10.1093/abbs/gmp098 Wellhoefer, 2013, Continuous processing of recombinant proteins: integration of inclusion body solubilization and refolding using simulated moving bed size exclusion chromatography with buffer recycling, J Chromatogr A, 1319, 107, 10.1016/j.chroma.2013.10.039 Tripathi, 2016, Production and purification of recombinant proteins from Escherichia coli, ChemBioEng Rev, 3, 116, 10.1002/cben.201600002 Birnboim, 1979, A rapid alkaline extraction procedure for screening recombinant plasmid DNA, Nucleic Acids Res, 7, 1513, 10.1093/nar/7.6.1513 Clemson, 2003, Optimizing alkaline lysis for DNA plasmid recovery, Biotechnol Appl Biochem, 37, 235, 10.1042/BA20030002 Diogo, 2005, Chromatography of plasmid DNA, J Chromatogr A, 1069, 3, 10.1016/j.chroma.2004.09.050 Endres, 2003, Evaluation of an ion-exchange membrane for the purification of plasmid DNA, Biotechnol Appl Biochem, 37, 259, 10.1042/BA20030025 Lin, 2005, Removal of lipopolysaccharides from protein-lipopolysaccharide complexes by nonflammable solvents, J Chromatogr B Analyt Technol Biomed Life Sci, 816, 167, 10.1016/j.jchromb.2004.11.029 Mhatre, 1995, Purification of antibody Fab fragments by cation-exchange chromatography and pH gradient elution, J Chromatogr A, 707, 225, 10.1016/0021-9673(95)00319-I Roque, 2005, An artificial protein L for the purification of immunoglobulins and fab fragments by affinity chromatography, J Chromatogr A, 1064, 157, 10.1016/j.chroma.2004.11.102 Zobel-Roos, 2019, Distinct and quantitative validation method for predictive process modelling in preparative chromatography of synthetic and bio-based feed mixtures following a quality-by-design (QbD) approach, Processes, 7, 580, 10.3390/pr7090580 Read, 2010, Process analytical technology (PAT) for biopharmaceutical products. Part I. Concepts and applications, Biotechnol Bioeng, 105, 276, 10.1002/bit.22528 Gomes, 2015, Integrating systems analysis and control for implementing process analytical technology in bioprocess development, J Chem Technol Biotechnol, 90 Rathore, 2010, Process analytical technology (PAT) for biopharmaceutical products, Anal Bioanal Chem, 398, 137, 10.1007/s00216-010-3781-x Glassey, 2011, Process analytical technology (PAT) for biopharmaceuticals, Biotechnol J, 6, 369, 10.1002/biot.201000356 Abu-Absi, 2014, Application of spectroscopic methods for monitoring of bioprocesses and the implications for the manufacture of biologics, Pharm Bioprocess, 2, 267, 10.4155/pbp.14.24 Lourenço, 2012, Bioreactor monitoring with spectroscopy and chemometrics: a review, Anal Bioanal Chem, 404, 1211, 10.1007/s00216-012-6073-9 Claßen, 2017, Spectroscopic sensors for in-line bioprocess monitoring in research and pharmaceutical industrial application, Anal Bioanal Chem, 409, 651, 10.1007/s00216-016-0068-x Krämer, 2017, A hybrid approach for bioprocess state estimation using NIR spectroscopy and a sigma-point Kalman filter, J Process Control Faassen, 2015, Fluorescence spectroscopy and chemometric modeling for bioprocess monitoring, Sensors, 15, 10271, 10.3390/s150510271 Odman, 2009, On-line estimation of biomass, glucose and ethanol in Saccharomyces cerevisiae cultivations using in-situ multi-wavelength fluorescence and software sensors, J Biotechnol, 144, 102, 10.1016/j.jbiotec.2009.08.018 Surribas, 2006, State variables monitoring by in situ multi-wavelength fluorescence spectroscopy in heterologous protein production by Pichia pastoris, J Biotechnol, 124, 412, 10.1016/j.jbiotec.2006.01.002 Jain, 2011, On-line monitoring of recombinant bacterial cultures using multi-wavelength fluorescence spectroscopy, Biochem Eng J, 58 Rathore, 2015, Application of process analytical technology for downstream purification of biotherapeutics, J Chem Technol Biotechnol, 90, 228, 10.1002/jctb.4447 Rathore, 2008, Case study and application of process analytical technology (PAT) towards bioprocessing. II. Use of ultra-performance liquid chromatography (UPLC) for making real-time pooling decisions for process chromatography, Biotechnol Bioeng, 101, 1366, 10.1002/bit.21982 Pizarro, 2010, High-yield expression of human vascular endothelial growth factor VEGF165 in Escherichia coli and purification for therapeutic applications, Protein Expr Purif, 72, 184, 10.1016/j.pep.2010.03.007 Rüdt, 2017, Advances in downstream processing of biologics – spectroscopy: an emerging process analytical technology, J Chromatogr A, 1490, 2, 10.1016/j.chroma.2016.11.010 Roch, 2019, vol. 2010 Walther, 2014, Getting ready for PAT: scale up and inline monitoring of protein refolding of Npro fusion proteins, Process Biochem, 49, 1113, 10.1016/j.procbio.2014.03.022 Lienqueo, 2012, Mathematical modeling of protein chromatograms, Chem Eng Technol, 35, 46, 10.1002/ceat.201100282 Delafosse, 2014, CFD-based compartment model for description of mixing in bioreactors, Chem Eng Sci, 106, 76, 10.1016/j.ces.2013.11.033 Zieringer, 2018, In silico prediction of large-scale microbial production performance: constraints for getting proper data-driven models, Comput Struct Biotechnol J, 16, 246, 10.1016/j.csbj.2018.06.002 Hajian, 2020, 1 Anane, 2019, A model-based framework for parallel scale-down fed-batch cultivations in mini-bioreactors for accelerated phenotyping, Biotechnol Bioeng, 116, 2906, 10.1002/bit.27116 Neubauer, 2010, Scale-down simulators for metabolic analysis of large-scale bioprocesses, Curr Opin Biotechnol, 21, 114, 10.1016/j.copbio.2010.02.001 Paul, 2020, Scale-down simulators for mammalian cell culture as tools to access the impact of inhomogeneities occurring in large-scale bioreactors, Eng Life Sci, 20, 197, 10.1002/elsc.201900162 Han, 2013, Design of growth-dependent biosensors based on destabilized GFP for the detection of physiological behavior of Escherichia coli in heterogeneous bioreactors, Biotechnol Prog, 29, 553, 10.1002/btpr.1694 Brognaux, 2013, Direct and indirect use of GFP whole cell biosensors for the assessment of bioprocess performances: design of milliliter scale-down bioreactors, Biotechnol Prog, 29, 48, 10.1002/btpr.1660 Kuschel, 2020, Simulated oxygen and glucose gradients as a prerequisite for predicting industrial scale performance a priori, Biotechnol Bioeng, 117, 2760, 10.1002/bit.27457 Sunya, 2012, Comparison of the transient responses of Escherichia coli to a glucose pulse of various intensities, Appl Microbiol Biotechnol, 95, 1021, 10.1007/s00253-012-3938-y Delvigne, 2018, Improving control in microbial cell factories: from single-cell to large-scale bioproduction, FEMS Microbiol Lett, 365 Spann, 2019, CFD predicted pH gradients in lactic acid bacteria cultivations, Biotechnol Bioeng, 10.1002/bit.26868 Bisgaard, 2020, Flow-following sensor devices: a tool for bridging data and model predictions in large-scale fermentations, Comput Struct Biotechnol J, 18, 2908, 10.1016/j.csbj.2020.10.004 Delvigne, 2014, Microbial heterogeneity affects bioprocess robustness: dynamic single-cell analysis contributes to understanding of microbial populations, Biotechnol J, 9, 61, 10.1002/biot.201300119 Delvigne, 2015, Dynamic single-cell analysis of Saccharomyces cerevisiae under process perturbation: comparison of different methods for monitoring the intensity of population heterogeneity, J Chem Technol Biotechnol, 90, 314, 10.1002/jctb.4430 Sassi, 2019, Segregostat: a novel concept to control phenotypic diversification dynamics on the example of Gram-negative bacteria, Microb Biotechnol, 12, 1064, 10.1111/1751-7915.13442 Janzen, 2019, Implementation of a fully automated microbial cultivation platform for strain and process screening, Biotechnol J, 14, 1800625, 10.1002/biot.201800625 Toeroek, 2015, Fed-batch like cultivation in a micro-bioreactor: screening conditions relevant for Escherichia coli based production processes, SpringerPlus, 4, 490, 10.1186/s40064-015-1313-z Burdick, 2017, Process design: stage 1 of the FDA process validation guidance, 115 Chung Chow, 2014, On assessment of analytical similarity in biosimilar studies, Drug Des Open Access, 03 Spann, 2018, Model-based process development for a continuous lactic acid bacteria fermentation, Comput Aided Chem Eng, 43, 1601, 10.1016/B978-0-444-64235-6.50279-5 ICH, 2020 Herwig, 2017, Better by design, Chem Eng Jameel, 2015 Telford, 2007, A brief introduction to design of experiments, Johns Hopkins Apl Tech Dig, 27, 224 Brueggemeier, 2012, Modeling-based approach towards quality by design for the ibipinabant API step, Org Process Res Dev, 16, 567, 10.1021/op2003024 Prpich, 2010, Drug product modeling predictions for scale-up of tablet film coating – a quality by design approach, Comput Chem Eng, 34, 1092, 10.1016/j.compchemeng.2010.03.006 García-Muñoz, 2015, Definition of design spaces using mechanistic models and geometric projections of probability maps, Org Process Res Dev, 19, 1012, 10.1021/acs.oprd.5b00158 Möller, 2020, Model uncertainty-based evaluation of process strategies during scale-up of biopharmaceutical processes, 106693Comput Chem Eng, 134 Möller, 2019, Model-assisted design of experiments as a concept for knowledge-based bioprocess development, Bioprocess Biosyst Eng, 42, 867, 10.1007/s00449-019-02089-7 Bano, 2019, Design space maintenance by online model adaptation in pharmaceutical manufacturing, Comput Chem Eng, 127, 254, 10.1016/j.compchemeng.2019.05.019 Continuous manufacturing in biotech processes – challenges for implementation. ISPE Int Soc Pharm Eng. http://www.ispe.org/pharmaceutical-engineering/november-december-2018/continuous-manufacturing-biotech-processes [accessed 16 June 2020]. Solle, 2017, Between the poles of data-driven and mechanistic modeling for process operation, Chem Ing Tech, 89, 542, 10.1002/cite.201600175 Spann, 2019, A compartment model for risk-based monitoring of lactic acid bacteria cultivations, Biochem Eng J, 151, 107293, 10.1016/j.bej.2019.107293 Sinner, 2019, Model-based analysis and optimisation of a continuous Corynebacterium glutamicum bioprocess utilizing lignocellulosic waste, IFAC-Pap, 52, 181 Amribt, 2013, Macroscopic modelling of overflow metabolism and model based optimization of hybridoma cell fed-batch cultures, Biochem Eng J, 70, 196, 10.1016/j.bej.2012.11.005 Scheiblauer, 2018, Fermentation of Saccharomyces cerevisiae – combining kinetic modeling and optimization techniques points out avenues to effective process design, J Theor Biol, 453, 125, 10.1016/j.jtbi.2018.05.016 Huuk, 2014, Model-based integrated optimization and evaluation of a multi-step ion exchange chromatography, Sep Purif Technol, 136, 207, 10.1016/j.seppur.2014.09.012 Anderson, 1976, Error propagation by the Monte Carlo method in geochemical calculations, Geochim Cosmochim Acta, 40, 1533, 10.1016/0016-7037(76)90092-2 Hofer, 2018, Metabolic flux analysis linked to complex raw materials as tool for bioprocess improvement, Chem Eng Sci, 191, 245, 10.1016/j.ces.2018.06.075 Krausch, 2019, Monte Carlo simulations for the analysis of non-linear parameter confidence intervals in optimal experimental design, Front Bioeng Biotechnol, 7, 10.3389/fbioe.2019.00122 Anane, 2019, Output uncertainty of dynamic growth models: effect of uncertain parameter estimates on model reliability, Biochem Eng J, 150, 107247, 10.1016/j.bej.2019.107247 Sin, 2009, Good modeling practice for PAT applications: propagation of input uncertainty and sensitivity analysis, Biotechnol Prog, 25, 1043, 10.1002/btpr.166 Biwer, 2005, Uncertainty analysis of penicillin V production using Monte Carlo simulation, Biotechnol Bioeng, 90, 167, 10.1002/bit.20359 Sommeregger, 2017, Quality by control: towards model predictive control of mammalian cell culture bioprocesses, Biotechnol J, 12, 10.1002/biot.201600546 Luttmann, 2012, Soft sensors in bioprocessing: a status report and recommendations, Biotechnol J, 7, 1040, 10.1002/biot.201100506 Herwig, 2001, On-line stoichiometry and identification of metabolic state under dynamic process conditions, Biotechnol Bioeng, 75, 345, 10.1002/bit.10058 Stelzer, 2017, Comparison of particle filter and extended Kalman filter algorithms for monitoring of bioprocesses, Comput Aided Chem Eng, 40, 1483, 10.1016/B978-0-444-63965-3.50249-X Papathanasiou, 2017, Advanced model-based control strategies for the intensification of upstream and downstream processing in mAb production, Biotechnol Prog, 33, 966, 10.1002/btpr.2483 Jelsch, 2021, Model predictive control in pharmaceutical continuous manufacturing: a review from a user’s perspective, Eur J Pharm Biopharm, 159, 137, 10.1016/j.ejpb.2021.01.003 Kroll, 2017, Model-based methods in the biopharmaceutical process lifecycle, Pharm Res, 34, 2596, 10.1007/s11095-017-2308-y Mandenius, 2015, Mini-review: soft sensors as means for PAT in the manufacture of bio-therapeutics, J Chem Technol Biotechnol, 90, 215, 10.1002/jctb.4477 Kroll, 2014, Ex situ online monitoring: application, challenges and opportunities for biopharmaceuticals processes, Pharm Bioprocess, 2, 285, 10.4155/pbp.14.22 Golabgir, 2015, Combining mechanistic modeling and Raman spectroscopy for real-time monitoring of fed-batch penicillin production, Chem Ing Tech Lecca, 2019, Identifying necessary and sufficient conditions for the observability of models of biochemical processes, Biophys Chem, 254, 106257, 10.1016/j.bpc.2019.106257 Golabgir, 2015, Observability analysis of biochemical process models as a valuable tool for the development of mechanistic soft sensors, Biotechnol Prog, 31, 1703, 10.1002/btpr.2176 Nakhaeinejad, 2011, Observability analysis for model-based fault detection and sensor selection in induction motors, Meas Sci Technol, 22, 075202, 10.1088/0957-0233/22/7/075202 Mou, 1983, Growth monitoring and control through computer-aided on-line mass balancing in a fed-batch penicillin fermentation, Biotechnol Bioeng, 25, 225, 10.1002/bit.260250118 Wechselberger, 2013, Real-time estimation of biomass and specific growth rate in physiologically variable recombinant fed-batch processes, Bioprocess Biosyst Eng, 36, 1205, 10.1007/s00449-012-0848-4 Aehle, 2011, Simplified off-gas analyses in animal cell cultures for process monitoring and control purposes, Biotechnol Lett, 33, 2103, 10.1007/s10529-011-0686-5 Luttmann, 2015, Sequential/parallel production of potential Malaria vaccines – a direct way from single batch to quasi-continuous integrated production, J Biotechnol, 213, 83, 10.1016/j.jbiotec.2015.02.022 Dabros, 2010, Simple control of specific growth rate in biotechnological fed-batch processes based on enhanced online measurements of biomass, Bioprocess Biosyst Eng, 33, 1109, 10.1007/s00449-010-0438-2 Jobe, 2003, Generally applicable fed-batch culture concept based on the detection of metabolic state by on-line balancing, Biotechnol Bioeng, 82, 627, 10.1002/bit.10610 Daume, 2020, Generic workflow for the setup of mechanistic process models, 189 Duan, 2020, Model reduction of aerobic bioprocess models for efficient simulation, Chem Eng Sci, 217, 115512, 10.1016/j.ces.2020.115512 Goffaux, 2005, Bioprocess state estimation: some classical and less classical approaches, 111 Simon, 2006 Simutis, 2014, State estimation of a biotechnological process using extended Kalman filter and particle filter, Int J Biol Food Vet Agric Eng, 8, 933 Sinner, 2020, Noninvasive online monitoring of Corynebacterium glutamicum fed-batch bioprocesses subject to spent sulfite liquor raw material uncertainty, Bioresour Technol, 124395 Destro, 2020, A hybrid framework for process monitoring: enhancing data-driven methodologies with state and parameter estimation, J Process Control, 92, 333, 10.1016/j.jprocont.2020.06.002 Kager, 2018, State estimation for a penicillin fed-batch process combining particle filtering methods with online and time delayed offline measurements, Chem Eng Sci, 177, 234, 10.1016/j.ces.2017.11.049 Guo, 2015, State estimation incorporating infrequent, delayed and integral measurements, Automatica, 58, 32, 10.1016/j.automatica.2015.05.001 Gopalakrishnan, 2011, Incorporating delayed and infrequent measurements in extended Kalman filter based nonlinear state estimation, J Process Control, 21, 119, 10.1016/j.jprocont.2010.10.013 del Rio-Chanona, 2016, Model-based real-time optimisation of a fed-batch cyanobacterial hydrogen production process using economic model predictive control strategy, Chem Eng Sci, 142, 289, 10.1016/j.ces.2015.11.043 Gudi, 1994, Multirate state and parameter estimation in an antibiotic fermentation with delayed measurements, Biotechnol Bioeng, 44, 1271, 10.1002/bit.260441102 Soons, 2007, Biomass growth and kLa estimation using online and offline measurements, CAB10 Comput Appl Biotechnol Cancun Smets, 2004, Optimal adaptive control of (bio)chemical reactors: past, present and future, J Process Control, 14, 795, 10.1016/j.jprocont.2003.12.005 Montague, 1989, Fermentation monitoring and control: a perspective, Biotechnol Genet Eng Rev, 7, 147, 10.1080/02648725.1989.10647858 Kager, 2020, Experimental verification and comparison of model predictive, PID and model inversion control in a Penicillium chrysogenum fed-batch process, Process Biochem, 90, 1, 10.1016/j.procbio.2019.11.023 Sagmeister, 2013, Soft-sensor assisted dynamic investigation of mixed feed bioprocesses, Process Biochem, 48, 1839, 10.1016/j.procbio.2013.09.018 Dewasme, 2015, State estimation and predictive control of fed-batch cultures of hybridoma cells, J Process Control, 30, 50, 10.1016/j.jprocont.2014.12.006 Mears, 2017, A review of control strategies for manipulating the feed rate in fed-batch fermentation processes, J Biotechnol, 245, 34, 10.1016/j.jbiotec.2017.01.008 Qin, 2003, A survey of industrial model predictive control technology, Control Eng Pract, 11, 733, 10.1016/S0967-0661(02)00186-7 Yoo, 2016, Optimization of microalgal photobioreactor system using model predictive control with experimental validation, Bioprocess Biosyst Eng, 39, 1235, 10.1007/s00449-016-1602-0 Ulonska, 2018, Model predictive control in comparison to elemental balance control in an E. coli fed-batch, Chem Eng Sci, 10.1016/j.ces.2018.06.074 Grossmann, 2010, Optimizing model predictive control of the chromatographic multi-column solvent gradient purification (MCSGP) process, J Process Control, 20, 618, 10.1016/j.jprocont.2010.02.013