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Gan J, Parulekar SJ. Multi-rate data-driven models for lactic acid fermentation - Parameter identification and prediction. Comput Chem Eng 2019. [DOI: 10.1016/j.compchemeng.2019.05.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Tabora JE, Domagalski N. Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development. Annu Rev Chem Biomol Eng 2017; 8:403-426. [DOI: 10.1146/annurev-chembioeng-060816-101418] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The application of statistics in pharmaceutical process research and development has evolved significantly over the past decades, motivated in part by the introduction of the Quality by Design paradigm, a landmark change in regulatory expectations for the level of scientific understanding associated with the manufacturing process. Today, statistical methods are increasingly applied to accelerate the characterization and optimization of new drugs created via numerous unit operations well known to the chemical engineering discipline. We offer here a review of the maturity in the implementation of design of experiment techniques, the increased incorporation of latent variable methods in process and material characterization, and the adoption of Bayesian methodology for process risk assessment.
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Affiliation(s)
- José E. Tabora
- Chemical & Synthetics Development, Pharmaceutical Development, Bristol-Myers Squibb Company, New Brunswick, New Jersey 08901;,
| | - Nathan Domagalski
- Chemical & Synthetics Development, Pharmaceutical Development, Bristol-Myers Squibb Company, New Brunswick, New Jersey 08901;,
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Shrivastava R, Mahalingam H, Dutta NN. Application and Evaluation of Random Forest Classifier Technique for Fault Detection in Bioreactor Operation. CHEM ENG COMMUN 2017. [DOI: 10.1080/00986445.2017.1292259] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Rahul Shrivastava
- Department of Chemical Engineering, Jaypee University of Engineering and Technology, Raghogarh, Guna (MP), India
| | - Hari Mahalingam
- Department of Chemical Engineering, National Institute of Technology Karnataka, Surathkal, India
| | - N. N. Dutta
- Department of Chemical Engineering, Jaypee University of Engineering and Technology, Raghogarh, Guna (MP), India
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Rajamanickam V, Wurm D, Slouka C, Herwig C, Spadiut O. A novel toolbox for E. coli lysis monitoring. Anal Bioanal Chem 2016; 409:667-671. [PMID: 27590321 PMCID: PMC5233743 DOI: 10.1007/s00216-016-9907-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 08/02/2016] [Accepted: 08/24/2016] [Indexed: 01/25/2023]
Abstract
The bacterium Escherichia coli is a well-studied recombinant host organism with a plethora of applications in biotechnology. Highly valuable biopharmaceuticals, such as antibody fragments and growth factors, are currently being produced in E. coli. However, the high metabolic burden during recombinant protein production can lead to cell death, consequent lysis, and undesired product loss. Thus, fast and precise analyzers to monitor E. coli bioprocesses and to retrieve key process information, such as the optimal time point of harvest, are needed. However, such reliable monitoring tools are still scarce to date. In this study, we cultivated an E. coli strain producing a recombinant single-chain antibody fragment in the cytoplasm. In bioreactor cultivations, we purposely triggered cell lysis by pH ramps. We developed a novel toolbox using UV chromatograms as fingerprints and chemometric techniques to monitor these lysis events and used flow cytometry (FCM) as reference method to quantify viability offline. Summarizing, we were able to show that a novel toolbox comprising HPLC chromatogram fingerprinting and data science tools allowed the identification of E. coli lysis in a fast and reliable manner. We are convinced that this toolbox will not only facilitate E. coli bioprocess monitoring but will also allow enhanced process control in the future.
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Affiliation(s)
- Vignesh Rajamanickam
- Research Division Biochemical Engineering, Institute of Chemical Engineering, Vienna University of Technology, Getreidemarkt 9/166, 1060, Vienna, Austria.,Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical Engineering, Vienna University of Technology, Gumpendorfer Strasse 1a, 1060, Vienna, Austria
| | - David Wurm
- Research Division Biochemical Engineering, Institute of Chemical Engineering, Vienna University of Technology, Getreidemarkt 9/166, 1060, Vienna, Austria
| | - Christoph Slouka
- Research Division Biochemical Engineering, Institute of Chemical Engineering, Vienna University of Technology, Getreidemarkt 9/166, 1060, Vienna, Austria
| | - Christoph Herwig
- Research Division Biochemical Engineering, Institute of Chemical Engineering, Vienna University of Technology, Getreidemarkt 9/166, 1060, Vienna, Austria.,Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical Engineering, Vienna University of Technology, Gumpendorfer Strasse 1a, 1060, Vienna, Austria
| | - Oliver Spadiut
- Research Division Biochemical Engineering, Institute of Chemical Engineering, Vienna University of Technology, Getreidemarkt 9/166, 1060, Vienna, Austria. .,Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical Engineering, Vienna University of Technology, Gumpendorfer Strasse 1a, 1060, Vienna, Austria.
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Mercier SM, Diepenbroek B, Wijffels RH, Streefland M. Multivariate PAT solutions for biopharmaceutical cultivation: current progress and limitations. Trends Biotechnol 2014; 32:329-36. [PMID: 24732022 DOI: 10.1016/j.tibtech.2014.03.008] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2013] [Revised: 03/10/2014] [Accepted: 03/10/2014] [Indexed: 02/06/2023]
Abstract
Increasingly elaborate and voluminous datasets are generated by the (bio)pharmaceutical industry and are a major challenge for application of PAT and QbD principles. Multivariate data analysis (MVDA) is required to delineate relevant process information from large multi-factorial and multi-collinear datasets. Here the key role of MVDA for industrial (bio)process data is discussed, with a focus on progress and limitations of MVDA as a PAT solution for biopharmaceutical cultivation processes. MVDA based models were proven useful and should be routinely implemented for bioprocesses. It is concluded that although the highest level of PAT with process control within its design space in real-time during manufacturing is not reached yet, MVDA will be central to reach this ultimate objective for cell cultivations.
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Affiliation(s)
- Sarah M Mercier
- Crucell Holland BV, Process Development Department, Archimedesweg 4-6, 2333 CN Leiden, The Netherlands
| | - Bas Diepenbroek
- Crucell Holland BV, Process Development Department, Archimedesweg 4-6, 2333 CN Leiden, The Netherlands
| | - Rene H Wijffels
- Wageningen University, Bioprocess Engineering, P.O. Box 8129, 6700 EV Wageningen, The Netherlands
| | - Mathieu Streefland
- Wageningen University, Bioprocess Engineering, P.O. Box 8129, 6700 EV Wageningen, The Netherlands.
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Gustavo Fe E, Valdes Vel R, Labate Val B, Goncalves A, Tonso A. Using Statistical Tools for Improving Bioprocesses. ACTA ACUST UNITED AC 2012. [DOI: 10.3923/ajbkr.2013.1.20] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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8
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Multivariate Data Analysis for Advancing the Interpretation of Bioprocess Measurement and Monitoring Data. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2012; 132:167-91. [DOI: 10.1007/10_2012_171] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Rathore AS, Bansal A, Hans J. Knowledge Management and Process Monitoring of Pharmaceutical Processes in the Quality by Design Paradigm. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2012; 132:217-47. [DOI: 10.1007/10_2012_172] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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Fault diagnosis of a benchmark fermentation process: a comparative study of feature extraction and classification techniques. Bioprocess Biosyst Eng 2011; 35:689-704. [DOI: 10.1007/s00449-011-0649-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2011] [Accepted: 10/27/2011] [Indexed: 10/15/2022]
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11
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Affiliation(s)
- Jerome Workman
- Unity Scientific LLC, 117 Old State Rd., Brookfield, Connecticut 06804, and United States National University, 11255 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Barry Lavine
- Department of Chemistry, Oklahoma State University, Stillwater, Oklahoma 74078, United States
| | - Ray Chrisman
- Atodyne Technologies, L.L.C., 4699 Pontiac Trail, Ann Arbor, Michigan 48105, United States
| | - Mel Koch
- Center for Process Analytical Chemistry (CPAC), University of Washington, Seattle, Washington 98195-1700, United States
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Horta ACL, da Silva AJ, Sargo CR, Gonçalves VM, Zangirolami TC, de Campos Giordano R. Robust artificial intelligence tool for automatic start-up of the supplementary medium feeding in recombinant E. coli cultivations. Bioprocess Biosyst Eng 2011; 34:891-901. [DOI: 10.1007/s00449-011-0540-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2010] [Accepted: 03/23/2011] [Indexed: 12/21/2022]
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