Soft sensors in bioprocessing: A status report and recommendations
Open accessAbstract
The following report with recommendations is the result of an expert panel meeting on soft sensor applications in bioprocess engineering that was organized by the Measurement, Monitoring, Modelling and Control (M3C) Working Group of the European Federation of Biotechnology ‐ Section of Biochemical Engineering Science (ESBES). The aim of the panel was to provide an update on the present status of the subject and to identify critical needs and issues for the furthering of the successful development of soft sensor methods in bioprocess engineering research and for industrial applications, in particular with focus on biopharmaceutical applications. It concludes with a set of recommendations, which highlight current prospects for the extended use of soft sensors and those areas requiring development.
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Designers of software sensors used in bioprocesses have to cope with variable process lengths, multiple process phases and especially faults of physical sensors used as inputs.
“There are, naturally, shortcomings as well: designers of software sensors used in bioprocesses have to cope with variable process lengths, multiple process phases and especially faults of physical sensors used as inputs.”
From Software sensors in the monitoring of microalgae cultivations (2024) · cites this paper as Luttmann et al. 2012
Section 4, “Industrial needs and opportunities for soft sensors in biochemical engineering” (page unavailable), says soft sensors must handle drift, outliers and missing data in analytical measurements, supporting the concern about unreliable sensor inputs. The passages do not identify variable process lengths or multiple process phases as design challenges, or establish that physical-sensor faults are especially important. (LLM, conf=0.78)
Experimental — accuracy not yet measuredSoftware sensors are commonly applied in all engineering disciplines, including bioprocess engineering.
“Software sensors are commonly applied in all the engineering disciplines (automotive and aircraft control, wastewater treatment, industrial-scale chemical processes such as distillation), including bioprocess engineering (Luttmann et al. 2012).”
From Software sensors in the monitoring of microalgae cultivations (2024) · cites this paper as Luttmann et al. 2012
The passage under “Monitor variability Analytes defined Monitor deviations” says soft sensors are widely used beyond bioprocesses and names automotive and aircraft control, wastewater treatment, and industrial-scale distillation—the citing sentence’s examples. It does not establish their use in *all* engineering disciplines. (LLM, conf=0.82)
Experimental — accuracy not yet measuredAll software sensors are observers in the broad sense of the word in control theory.
“Generally, all software sensors are observers in the broad sense of the word in control theory (Luttmann et al. 2012; Aguilar-Garnica and García-Sandoval 2015).”
From Software sensors in the monitoring of microalgae cultivations (2024) · cites this paper as Luttmann et al. 2012
Section 2 (‘What is a soft sensor? A definition’; page unavailable) describes soft sensors as using accessible data to estimate other variables and says ‘observer-based sensors’ may be an appropriate term. It does not state that all software sensors are observers in the control-theory sense; its qualified terminology does not establish that universal claim. (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe development of software sensors can be carried out using two different types of methodologies: model-driven estimators and data-driven estimators.
“In general, the development of software sensors can be carried out using two different types of methodologies: model-driven estimators and data-driven estimators, which are terms generally accepted in the literature (Kadlec et al. 2009; Luttmann et al. 2012).”
From Software sensors in the monitoring of microalgae cultivations (2024) · cites this paper as Luttmann et al. 2012
In 2012, a report on soft sensors in bioprocessing was issued by the European Federation of Biotechnology, which identified critical needs and issues and concluded with a set of eight recommendations.
“In 2012, a report on soft sensors in bioprocessing was issued by the European Federation of Biotechnology, which identified critical needs and issues for the successful development of soft sensor methods in bioprocess research and industry and concluded with a set of eight recommendations highlighting areas requiring development (Luttmann et al. 2012).”
From Software sensors in the monitoring of microalgae cultivations (2024) · cites this paper as Luttmann et al. 2012
The European Federation of Biotechnology (EFB) Section on Biochemical Engineering Science (ESBES) refers to a similar philosophy of Modelling, Monitoring, Measurement & Control (M3C).
“The European Federation of Biotechnology (EFB) Section on Biochemical Engineering Science (ESBES) refers to a similar philosophy of Modelling, Monitoring, Measurement & Control (M3C) [14,15].”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [14]
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Cites
Data-driven Soft Sensors in the process industry
Kadlec, P., Gabrys, B., & Strandt, S. (2009) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2008.12.012 · Cited by 1,845 · see citing works
Process analytical technology (PAT) for biopharmaceuticals
Glassey, J., Gernaey, K. V., Clemens, C., Schulz, T. W., Oliveira, R., Striedner, G., & Mandenius, C. (2011) · Biotechnology Journal · doi:10.1002/biot.201000356 · Cited by 212 · see citing works
Self-citationChoi, D.-J., & Park, H. (2001) · Water Research · doi:10.1016/s0043-1354(01)00134-8 · Cited by 188 · see citing works
Biomass measurement online: the performance of in situ measurements and software sensors
Kiviharju, K., Salonen, K., Moilanen, U., & Eerikäinen, T. (2008) · Journal of Industrial Microbiology & Biotechnology · doi:10.1007/s10295-008-0346-5 · Cited by 173 · see citing works
In‐situ near infrared spectroscopy to monitor key analytes in mammalian cell cultivation
Arnold, S. A., Crowley, J. N., Woods, N., Harvey, L. M., & McNeil, B. W. J. (2003) · Biotechnology and Bioengineering · doi:10.1002/bit.10738 · Cited by 149 · see citing works
Software sensors in bioprocess engineering
Chéruy, A. (1997) · Journal of Biotechnology · doi:10.1016/s0168-1656(96)01644-6 · Cited by 136 · see citing works
Near Infrared Spectroscopy for Bioprocess Monitoring and Control: Current Status and Future Trends
Scarff, M., Arnold, S. A., Harvey, L. M., & McNeil, B. (2006) · Critical Reviews in Biotechnology · doi:10.1080/07388550500513677 · Cited by 124 · see citing works
Self-Validating Inferential Sensors with Application to Air Emission Monitoring
Qin, S. J., Yue, H., & Dunia, R. (1997) · Industrial & Engineering Chemistry Research · doi:10.1021/ie960615y · Cited by 111 · see citing works
Ödman, P., Johansen, C. L., Lisbeth Olsson, A., Gernaey, K. V., & Lantz, A. E. (2009) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2009.08.018 · Cited by 97 · see citing works
Self-citationNavrátil, M., Norberg, A., Lembrén, L., & Mandenius, C. (2004) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2004.07.013 · Cited by 86 · see citing works
Self-citationEnhancing bioprocess operability with generic software sensors
Montague, G. A., Morris, A. J., & Tham, M. T. (1992) · Journal of Biotechnology · doi:10.1016/0168-1656(92)90114-o · Cited by 80 · see citing works
Roychoudhury, P., O’Kennedy, R. D., McNeil, B. W. J., & Harvey, L. M. (2007) · Analytica Chimica Acta · doi:10.1016/j.aca.2007.03.011 · Cited by 77 · see citing works
Recent developments in the monitoring, modeling and control of biological production systems
Mandenius, C. (2004) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-004-0383-z · Cited by 76 · see citing works
Self-citationJiang, C., Flansburg, L., Ghose, S., Jorjorian, P., & Shukla, A. (2010) · Biotechnology and Bioengineering · doi:10.1002/bit.22894 · Cited by 75 · see citing works
Estimating product composition profiles in batch distillation via partial least squares regression
Zamprogna, E., Barolo, M., & Seborg, D. E. (2004) · Control Engineering Practice · doi:10.1016/j.conengprac.2003.11.005 · Cited by 67 · see citing works
Intelligent integrated plant operation system for Six Sigma
Han, C., & Lee, Y.-H. (2002) · Annual Reviews in Control · doi:10.1016/s1367-5788(02)80008-6 · Cited by 63 · see citing works
Quality‐by‐Design for biotechnology‐related pharmaceuticals
Mandenius, C., Graumann, K., Schultz, T. W., Premstaller, A., Olsson, I., Petiot, E., Clemens, C., & Welin, M. (2009) · Biotechnology Journal · doi:10.1002/biot.200800333 · Cited by 63 · see citing works
Self-citationBioanalytics: detailed insight into bioprocesses
Scheper, T. H., Hitzmann, B., Stärk, E., Ulber, R., Faurie, R., Sosnitza, P., & Reardon, K. F. (1999) · Analytica Chimica Acta · doi:10.1016/s0003-2670(99)00612-1 · Cited by 60 · see citing works
Monitoring the Glycosylation Status of Proteins Using Raman Spectroscopy
Brewster, V. L., Ashton, L., & Goodacre, R. (2011) · Analytical Chemistry · doi:10.1021/ac2012009 · Cited by 60 · see citing works
Sellick, C. A., Hansen, R., Jarvis, R. M., Maqsood, A. R., Stephens, G., Dickson, A. J., & Goodacre, R. (2010) · Biotechnology and Bioengineering · doi:10.1002/bit.22707 · Cited by 60 · see citing works
Advanced Instrumentation, Data Interpretation, and Control of Biotechnological Processes
van Impe, J. F. M., Vanrolleghem, P. A., & Iserentant, D. (1998) · Springer eBooks · doi:10.1007/978-94-015-9111-9 · Cited by 59 · see citing works
Monitoring batch fermentations with an electronic tongue
Turner, C., Rudnitskaya, A. M., & Legin, A. V. (2003) · Journal of Biotechnology · doi:10.1016/s0168-1656(03)00066-x · Cited by 59 · see citing works
Simplified off-gas analyses in animal cell cultures for process monitoring and control purposes
Aehle, M., Kuprijanov, A., Schaepe, S., Simutis, R., & Lübbert, A. (2011) · Biotechnology Letters · doi:10.1007/s10529-011-0686-5 · Cited by 58 · see citing works
Software sensors for fermentation processes
Sundström, H., & Enfors, S. (2007) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-007-0157-5 · Cited by 54 · see citing works
Enhanced supervision of recombinant E. coli fermentation via artificial neural networks
Glassey, J., Montague, G. A., Ward, A. C., & Kara, B. (1994) · Process Biochemistry · doi:10.1016/0032-9592(94)87009-8 · Cited by 53 · see citing works
Self-citationInstrumentation of Biotechnological Processes
Sonnleitner, B. (1999) · Advances in biochemical engineering, biotechnology · doi:10.1007/3-540-48773-5_1 · Cited by 52 · see citing works
Warth, B., Rajkai, G., & Mandenius, C. (2010) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2010.02.023 · Cited by 45 · see citing works
Self-citationBiomass Estimation in Plant Cell Cultures Using an Extended Kalman Filter
Albiol, J., Robusté, J., Casas, C., & Manel Poch, A. (1993) · Biotechnology Progress · doi:10.1021/bp00020a009 · Cited by 45 · see citing works
Cunha, C., Glassey, J., Montague, G. A., Albert, S. M., & Mohan, P. (2002) · Biotechnology and Bioengineering · doi:10.1002/bit.10258 · Cited by 44 · see citing works
Self-citationComprehensive Quality Evaluation of Corn Steep Liquor in 2-Keto- l -gulonic Acid Fermentation
Gao, Y., & Yuan, Y. (2011) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf201792u · Cited by 42 · see citing works
Searching for process information in the aroma of cell cultures
Bachinger, T. (2000) · Trends in biotechnology · doi:10.1016/s0167-7799(00)01512-2 · Cited by 39 · see citing works
A multi‐bioreactor system for optimal production of malaria vaccines with Pichia pastoris
Fricke, J., Pohlmann, K., Tatge, F., Lang, R., Faber, B. W., & Luttmann, R. (2011) · Biotechnology Journal · doi:10.1002/biot.201000385 · Cited by 24 · see citing works
Self-citationPredicting the performance of soft sensors as a route to low cost automation
Goodwin, G. C. (2000) · Annual Reviews in Control · doi:10.1016/s1367-5788(00)90013-0 · Cited by 22 · see citing works
Multivariate statistical methods in bioprocess fault detection and performance forecasting
Ignova, M., Glassey, J., Ward, A. C., & Montague, G. A. (1997) · Transactions of the Institute of Measurement and Control · doi:10.1177/014233129701900507 · Cited by 21 · see citing works
Self-citationPredicting the Performance of Soft Sensors as a Route to Low Cost Automation
Goodwin, G. (2000) · Annual Reviews in Control · doi:10.1016/s1367-5788(00)00012-2 · Cited by 16 · see citing works
Application of agent‐based system for bioprocess description and process improvement
Gao, Y., Kipling, K., Glassey, J., Willis, M. J., Montague, G. A., Zhou, Y., & Titchener-Hooker, N. J. (2009) · Biotechnology Progress · doi:10.1002/btpr.361 · Cited by 15 · see citing works
Self-citationProduction of Recombinant Proteins with Pichia pastoris in Integrated Processing
Cornelissen, G., Bertelsen, H. ‐., Lenz, K., Hahn, B., Schultz, M., Scheffler, U., Werner, E., Leptien, H., Krüß, S., Jansen, A. ‐., et al. (2003) · Engineering in Life Sciences · doi:10.1002/elsc.200300033 · Cited by 15 · see citing works
Self-citationBracewell, D. G., Brown, R. A., & Hoare, M. (2004) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-004-0359-z · Cited by 13 · see citing works
Self-citationDevelopment of control strategies for high cell density cultivations
Luttmann, R., Bitzer, G., & Hartkopf, J. (1994) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(94)00004-2 · Cited by 12 · see citing works
Self-citationPeuker, T., Riedel, M., Kaiser, C., Ellert, A., Lenz, K., Elsholz, O., & Luttmann, R. (2004) · Engineering in Life Sciences · doi:10.1002/elsc.200401910 · Cited by 8 · see citing works
Self-citationFargestad, E. M., Øyaas, J., Köhler, A., Berg, T., & Næs, T. (2011) · LWT · doi:10.1016/j.lwt.2011.05.014 · Cited by 6 · see citing works
Zamprogna, E., Barolo, M., & Seborg, D. E. (2002) · IFAC Proceedings Volumes · doi:10.3182/20020721-6-es-1901.00483 · Cited by 6 · see citing works
Bioreaction Engineering:Bioprocess monitoring.Volume 3
Schügerl, K. (1997) · Cited by 4 · see citing works
Papini, M., Lisbeth Olsson, A., Lantz, A. E., van den Berg, F. W. J., Leuenhagen, C., & Wiertz, M. (2007) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2007.07.924 · Cited by 1 · see citing works
Flagged first, then by citations
1 of the 45 references couldn’t be matched to a known paper.
Research works printed but not linked: 6
- [2]2. Sonnleitner, B., Instrumentation of biotechnological pro - cesses. Adv. Biochem. Eng. Biotechnol. 1999, 66, 1-64.
- [6]6. International conference on Harmonization (ICH) Docu- ment ICH Q8-Q10, 2005-2010. Available at www.ich.org.
- [7]7. Glassey J., Gernaey K.V., Oliveria R., Striedner G. et al., PAT for biopharmaceuticals. Biotechnol. J. 2011, 6, 369-377.
- [8]8. Mandenius C.-F., Graumann K., Schultz T. W., Premsteller A., et al., Quality-by-Design (QbD) for biotechnology-relat- ed phamaceuticals. Biotechnol. J. 2009, 4, 600-609.
- [26]26. Kaiser, C., Carvell, J. P., Luttmann, R., A sensitive, compact, in situ biomass measurement system. BioProc. Intern. 2007, 5, 52-56.
- [35]35. Bracewell D.G., Brown R.A., Hoare M., Addressing a whole bioprocess in real-time using an optical biosensor -from a recombinant E. coli host. Bioproc. Biosys. Eng. 2004, 26, 271- 282.
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Assessment of Recent Process Analytical Technology (PAT) Trends: A Multiauthor Review
Simon, L. L., Pataki, H., Marosi, G., Meemken, F., Hungerbühler, K., Baiker, A., Tummala, S., Glennon, B., Kuentz, M., Steele, G., et al. (2015) · Organic Process Research & Development · doi:10.1021/op500261y · Cited by 445 · see citing works
Self-citationCultivation strategies to enhance productivity of Pichia pastoris: A review
Looser, V., Bruhlmann, B., Bumbak, F., Stenger, C., Costa, M., Camattari, A., Fotiadis, D., & Kovar, K. (2015) · Biotechnology Advances · doi:10.1016/j.biotechadv.2015.05.008 · Cited by 350 · see citing works
Esmonde-White, K. A., Cuellar, M., Uerpmann, C., Lenain, B., & Lewis, I. R. (2017) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-016-9824-1 · Cited by 332 · see citing works
Bioprocessing in the Digital Age: The Role of Process Models
Narayanan, H., Luna, M. F., von Stosch, M., Bournazou, M. N. C., Polotti, G., Morbidelli, M., Butté, A., & Sokolov, M. (2019) · Biotechnology Journal · doi:10.1002/biot.201900172 · Cited by 254 · see citing works
Sensor systems for bioprocess monitoring
Biechele, P., Busse, C., Solle, D., Scheper, T., & Reardon, K. (2015) · Engineering in Life Sciences · doi:10.1002/elsc.201500014 · Cited by 224 · see citing works
A review of control strategies for manipulating the feed rate in fed-batch fermentation processes
Mears, L., Stocks, S. M., Sin, G., & Gernaey, K. V. (2017) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2017.01.008 · Cited by 199 · see citing works
Self-citationMachine learning in bioprocess development: from promise to practice
Helleckes, L. M., Hemmerich, J., Wiechert, W., von Lieres, E., & Grünberger, A. (2022) · Trends in biotechnology · doi:10.1016/j.tibtech.2022.10.010 · Cited by 175 · see citing works
Artificial intelligence and machine learning applications in biopharmaceutical manufacturing
Rathore, A. S., Nikita, S., Thakur, G., & Mishra, S. (2022) · Trends in biotechnology · doi:10.1016/j.tibtech.2022.08.007 · Cited by 166 · see citing works
Quality by control: Towards model predictive control of mammalian cell culture bioprocesses
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Goldrick, S., Ştefan, A., Lovett, D., Montague, G. A., & Lennox, B. (2014) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2014.10.029 · Cited by 143 · see citing works
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Khuat, T. T., Bassett, R., Otte, E. A., Grevis-James, A., & Gabryś, B. (2024) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2024.108585 · Cited by 98 · see citing works
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Carrondo, M. J. T., Alves, P. M., Carinhas, N., Glassey, J., Hesse, F., Merten, O., Micheletti, M., Noll, T., Oliveira, R., Reichl, U., et al. (2012) · Biotechnology Journal · doi:10.1002/biot.201200226 · Cited by 59 · see citing works
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Self-citationBaradez, M.-O., Biziato, D., Hassan, E., & Marshall, D. (2018) · Frontiers in Medicine · doi:10.3389/fmed.2018.00047 · Cited by 55 · see citing works
Benchmarking real-time monitoring strategies for ethanol production from lignocellulosic biomass
López, P. C., Feldman, H., Mauricio‐Iglesias, M., Junicke, H., Huusom, J. K., & Gernaey, K. V. (2019) · Biomass and Bioenergy · doi:10.1016/j.biombioe.2019.105296 · Cited by 75 · see citing works
Self-citationA review on soft pneumatic actuators with integrated or embedded soft sensors
Gariya, N., Kumar, S., Shaikh, A., Prasad, B., & Nautiyal, H. (2024) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2024.115364 · Cited by 55 · see citing works
Bayer, B., Diaz, R. D., Melcher, M., Striedner, G., & Duerkop, M. (2021) · Processes · doi:10.3390/pr9071109 · Cited by 47 · see citing works
Self-citationPappenreiter, M., Sissolak, B., Sommeregger, W., & Striedner, G. (2019) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2019.00195 · Cited by 52 · see citing works
Self-citationSoftware sensors in the monitoring of microalgae cultivations
Porras Reyes, L., Havlik, I., & Beutel, S. (2024) · Reviews in Environmental Science and Bio/Technology · doi:10.1007/s11157-023-09679-8 · Cited by 48 · see citing works
“…issued by the European Federation of Biotechnology, which identified critical needs and issues for the successful development of soft sensor methods in bioprocess research and industry and concluded with a set of eight recommendations highlighting areas requiring development (Luttmann et al. 2012).”
InfluentialRefolding in the modern biopharmaceutical industry
Buscajoni, L., Martinetz, M. C., Berkemeyer, M., & Brocard, C. (2022) · Biotechnology Advances · doi:10.1016/j.biotechadv.2022.108050 · Cited by 48 · see citing works
Golabgir, A., & Herwig, C. (2016) · Chemie Ingenieur Technik · doi:10.1002/cite.201500101 · Cited by 47 · see citing works
Konakovsky, V., Clemens, C., Müller, M., Bechmann, J., Berger, M., Schlatter, S., & Herwig, C. (2016) · Bioengineering · doi:10.3390/bioengineering3010005 · Cited by 44 · see citing works
Practical monitoring technologies for cells and substrates in biomanufacturing
Reardon, K. F. (2021) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2021.08.006 · Cited by 44 · see citing works
Workflow to set up substantial target-oriented mechanistic process models in bioprocess engineering
Kröll, P., Hofer, A., Stelzer, I. V., & Herwig, C. (2017) · Process Biochemistry · doi:10.1016/j.procbio.2017.07.017 · Cited by 43 · see citing works
Kager, J., Tuveri, A., Ulonska, S., Kröll, P., & Herwig, C. (2019) · Process Biochemistry · doi:10.1016/j.procbio.2019.11.023 · Cited by 42 · see citing works
A Soft Sensor for Bioprocess Control Based on Sequential Filtering of Metabolic Heat Signals
Paulsson, D., Gustavsson, R., & Mandenius, C. (2014) · Sensors · doi:10.3390/s141017864 · Cited by 41 · see citing works
Self-citationAdvanced Process and Control Strategies for Bioreactors
Pörtner, R., Barradas, O. P., Frahm, B., & Hass, V. C. (2016) · Elsevier eBooks · doi:10.1016/b978-0-444-63663-8.00016-1 · Cited by 41 · see citing works
Self-citationOn-line monitoring of downstream bioprocesses
Roch, P., & Mandenius, C. (2016) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2016.09.007 · Cited by 41 · see citing works
Self-citationOhadi, K., Legge, R. L., & Budman, H. M. (2014) · Biotechnology and Bioengineering · doi:10.1002/bit.25339 · Cited by 41 · see citing works
Glassey, J. (2012) · Advances in biochemical engineering, biotechnology · doi:10.1007/10_2012_171 · Cited by 40 · see citing works
Self-citationTunable recombinant protein expression in E. coli: enabler for continuous processing?
Marschall, L., Sagmeister, P., & Herwig, C. (2016) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-016-7550-4 · Cited by 40 · see citing works
Armstrong, A., Horry, K., Cui, T., Hulley, M. E., Turner, R. C., Farid, S. S., Goldrick, S., & Bracewell, D. G. (2021) · Journal of Chromatography A · doi:10.1016/j.chroma.2021.461914 · Cited by 40 · see citing works
Self-citationPodevin, M., Fotidis, I. A., & Angelidaki, I. (2018) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2017.1398132 · Cited by 34 · see citing works
Barchi, A. C., Ito, S., Escaramboni, B., Neto, P. D. O., Herculano, R. D., Miranda, M. C. R., Passalia, F. J., Rocha, J. C., & Núñez, E. G. F. (2016) · Process Biochemistry · doi:10.1016/j.procbio.2016.07.017 · Cited by 33 · see citing works
Rathore, A. S., Nikita, S., & Jesubalan, N. G. (2022) · Biosensors and Bioelectronics X · doi:10.1016/j.biosx.2022.100263 · Cited by 33 · see citing works
Industrial internet of things: What does it mean for the bioprocess industries?
Borgosz, L., & Dikicioǧlu, D. (2023) · Biochemical Engineering Journal · doi:10.1016/j.bej.2023.109122 · Cited by 32 · see citing works
Holzberg, T. R., Watson, V. E., Brown, S., Andar, A. U., Ge, X., Kostov, Y. V., Tolosa, L. M., & Rao, G. (2018) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2018.09.008 · Cited by 31 · see citing works
Zitzmann, J., Weidner, T., Eichner, G., Salzig, D., & Czermak, P. (2018) · Sensors · doi:10.3390/s18030900 · Cited by 32 · see citing works
On digital twins in bioprocessing: Opportunities and limitations
Shariatifar, M., Rizi, M. S., Sotudeh‐Gharebagh, R., Zarghami, R., & Mostoufi, N. (2025) · Process Biochemistry · doi:10.1016/j.procbio.2025.05.023 · Cited by 32 · see citing works
Soft sensor for monitoring biomass subpopulations in mammalian cell culture processes
Kröll, P., Stelzer, I. V., & Herwig, C. (2017) · Biotechnology Letters · doi:10.1007/s10529-017-2408-0 · Cited by 31 · see citing works
Richelle, A., David, B., Demaegd, D., Dewerchin, M., Kinet, R., Morreale, A., Portela, R. M. C., Zune, Q., & von Stosch, M. (2020) · npj Systems Biology and Applications · doi:10.1038/s41540-020-0127-y · Cited by 31 · see citing works
Dynamic soft sensor development based on Gaussian mixture regression for fermentation processes
Mei, C., Su, Y. J., Liu, G., Ding, Y., & Liao, Z. (2016) · Chinese Journal of Chemical Engineering · doi:10.1016/j.cjche.2016.07.005 · Cited by 30 · see citing works
Chopda, V., Gomes, J., & Rathore, A. S. (2015) · Biotechnology Journal · doi:10.1002/biot.201500507 · Cited by 30 · see citing works
A probabilistic model-based soft sensor to monitor lactic acid bacteria fermentations
Spann, R., Roca, C., Kold, D., Lantz, A. E., Gernaey, K. V., & Sin, G. (2018) · Biochemical Engineering Journal · doi:10.1016/j.bej.2018.03.016 · Cited by 29 · see citing works
Self-citationGolabgir, A., Hoch, T., Zhariy, M., & Herwig, C. (2015) · Biotechnology Progress · doi:10.1002/btpr.2176 · Cited by 28 · see citing works
Gustavsson, R., & Mandenius, C. (2012) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-012-0840-z · Cited by 27 · see citing works
Self-citationBrignoli, Y., Freeland, B. H., Cunningham, D., & Dabros, M. (2020) · Processes · doi:10.3390/pr8060679 · Cited by 26 · see citing works
Advances in monitoring and control of refolding kinetics combining PAT and modeling
Pauk, J. N., Raju Palanisamy, J., Kager, J., Koczka, K., Berghammer, G., Herwig, C., & Veiter, L. (2021) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-021-11151-y · Cited by 25 · see citing works
Gasset, A., G., V. W. J. B., Mirabent, F., Sales‐Vallverdú, A., Garcia‐Ortega, X., Montesinos, J. L. G., Manzano, T., & Valero, F. (2024) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2024.1439638 · Cited by 25 · see citing works
Melo, B. H. D. S., Sales, R. F., Filho, L. D. S. B., da Silva, J. S. P., Sousa, A. G. C. D. A., Peixoto, D. M. C., & Pimentel, M. F. (2021) · Food Chemistry · doi:10.1016/j.foodchem.2021.130919 · Cited by 25 · see citing works
Sensors and chemometrics in downstream processing
Dürauer, A., Jungbauer, A., & Scharl, T. (2023) · Biotechnology and Bioengineering · doi:10.1002/bit.28499 · Cited by 30 · see citing works
Shall we use hardware sensor measurements or soft-sensor estimates? Case study in a full-scale WWTP
Haimi, H., Corona, F., Mulas, M., Sundell, L., Heinonen, M., & Vahala, R. (2015) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2015.07.013 · Cited by 25 · see citing works
Identifying and eliminating cell culture process variability
Gilbert, A., Huang, Y., & Ryll, T. (2014) · Pharmaceutical Bioprocessing · doi:10.4155/pbp.14.35 · Cited by 25 · see citing works
Knowledge management in a waste based biorefinery in the QbD paradigm
Rathore, A. S., Chopda, V., & Gomes, J. (2016) · Bioresource Technology · doi:10.1016/j.biortech.2016.03.168 · Cited by 25 · see citing works
Trends in Process Analytical Technology: Present State in Bioprocessing
Jenzsch, M., Bell, C., Buziol, S., Kepert, F., Wegele, H., & Hakemeyer, C. (2017) · Advances in biochemical engineering, biotechnology · doi:10.1007/10_2017_18 · Cited by 24 · see citing works
Cogoni, G., Liu, Y. A., Husain, A., Alam, M. A., & Kamyar, R. (2021) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2021.120620 · Cited by 24 · see citing works
Monitoring fermentation processes using in‐process measurements of different orders
Svendsen, C., Skov, T., & van den Berg, F. W. J. (2014) · Journal of Chemical Technology & Biotechnology · doi:10.1002/jctb.4483 · Cited by 24 · see citing works
Soft-sensor assisted dynamic investigation of mixed feed bioprocesses
Sagmeister, P., Kment, M., Wechselberger, P., Meitz, A., Langemann, T., & Herwig, C. (2013) · Process Biochemistry · doi:10.1016/j.procbio.2013.09.018 · Cited by 23 · see citing works
Mears, L., Stocks, S. M., Albæk, M. O., Sin, G., & Gernaey, K. V. (2016) · Biotechnology and Bioengineering · doi:10.1002/bit.26187 · Cited by 23 · see citing works
Self-citationTowards digitalization of hydraulic systems using soft sensor networks
Pelz, P. F., Dietrich, I., Schänzle, C., & Preuß, N. (2018) · Technischen Universität Darmstadt · doi:10.18154/rwth-2018-224546 · Cited by 22 · see citing works
Niazi, S. K. (2025) · Pharmaceuticals · doi:10.3390/ph18081157 · Cited by 22 · see citing works
Real‐time optimization and control for polyhydroxybutyrate fed‐batch production at pilot plant scale
Ochoa, S., García, C. A., & Zapata, W. A. (2020) · Journal of Chemical Technology & Biotechnology · doi:10.1002/jctb.6500 · Cited by 22 · see citing works
Challenges for Bioreactor Design and Operation
Mandenius, C. (2016) · doi:10.1002/9783527683369.ch1 · Cited by 22 · see citing works
Self-citationRydal, T., Frandsen, J. R., Nadal‐Rey, G., Albæk, M. O., & Ramin, P. (2024) · Biotechnology and Bioengineering · doi:10.1002/bit.28670 · Cited by 21 · see citing works
Noise-Tolerant Co-Trained Semisupervised Soft Sensor Model for Industrial Process
Lei, Q., & Wang, H. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3201706 · Cited by 21 · see citing works
On-line monitoring of process parameters during fermentation
Gargalo, C. L., López, P. C., Hasanzadeh, A., Udugama, I. A., & Gernaey, K. V. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91167-2.00003-4 · Cited by 21 · see citing works
Self-citationDownstream processing for influenza vaccines and candidates: An update
Carvalho, S. B., Peixoto, C., Carrondo, M. J. T., & Silva, R. J. S. (2021) · Biotechnology and Bioengineering · doi:10.1002/bit.27803 · Cited by 21 · see citing works
Brunner, V., Siegl, M., Geier, D., & Becker, T. M. (2020) · Biotechnology and Bioengineering · doi:10.1002/bit.27454 · Cited by 20 · see citing works
Cheng, X., Yu, Z., Wang, G., Jiang, Q., & Cao, Z. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.109065 · Cited by 19 · see citing works
Pontius, K., Junicke, H., Gernaey, K. V., & Bevilacqua, M. (2020) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-020-10604-0 · Cited by 19 · see citing works
Self-citationPropagation of measurement accuracy to biomass soft-sensor estimation and control quality
Steinwandter, V., Zahel, T., Sagmeister, P., & Herwig, C. (2016) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-016-9711-9 · Cited by 18 · see citing works
Monitoring and Control of Bioreactor: Basic Concepts and Recent Advances
Gomes, J., Chopda, V., & Rathore, A. S. (2018) · doi:10.1002/9781119378341.ch6 · Cited by 18 · see citing works
- Authors
- Luttmann, R., Bracewell, D. G., Cornelissen, G., Gernaey, K. V., Glassey, J., Hass, V. C., Kaiser, C., Preusse, C., Striedner, G., & Mandenius, C.
- Affiliations
- HAW Hamburg (DE)
- University College London (GB)
- Technical University of Denmark (DK)
- Newcastle University (GB)
- Hochschule Bremen (DE)
- Siemens (Germany) (DE)
- BOKU University (AT)
- Linköping University (SE)
- Corresponding author
- Mandenius, Carl‐Fredrik
- Venue
- Biotechnology Journal
- Publisher
- Wiley
- Published
- 2012-04-05
- Volume
- 7
- Issue
- 8
- Pages
- 1040-1048
- ISSN
- 1860-6768 (ISSN-L)
- 1860-7314
- OpenAlex
- W1976208842
- Semantic Scholar
- 0e818465623055f53ab0e6d030d60c113dcb2804
- Cited by
- 238
- References
- 45
- Citations by year
- 2026: 12 · 2025: 13 · 2024: 17 · 2023: 9 · 2022: 21 · 2021: 24 · 2020: 31 · 2019: 14 · 2018: 16 · 2017: 18 · 2016: 24 · 2015: 13 · 2014: 14 · 2013: 4 · 2012: 7
- FWCI
- 17.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Biotechnology Journal (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Repository of Futwangen University of Applied Sciences (Furtwangen University) (submittedVersion)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Keywords
- soft sensors, bioprocess monitoring, bioprocess engineering, biopharmaceutical manufacturing, process analytical technology, process control, expert panel recommendations
- MeSH terms
- Biotechnology, Chemical Engineering, Models, Theoretical, Software, Biosensing Techniques, Bioreactors, Bioengineering
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