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Sripada SA, Hosseini M, Ramesh S, Wang J, Ritola K, Menegatti S, Daniele MA. Advances and opportunities in process analytical technologies for viral vector manufacturing. Biotechnol Adv 2024; 74:108391. [PMID: 38848795 DOI: 10.1016/j.biotechadv.2024.108391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 03/14/2024] [Accepted: 05/29/2024] [Indexed: 06/09/2024]
Abstract
Viral vectors are an emerging, exciting class of biologics whose application in vaccines, oncology, and gene therapy has grown exponentially in recent years. Following first regulatory approval, this class of therapeutics has been vigorously pursued to treat monogenic disorders including orphan diseases, entering hundreds of new products into pipelines. Viral vector manufacturing supporting clinical efforts has spurred the introduction of a broad swath of analytical techniques dedicated to assessing the diverse and evolving panel of Critical Quality Attributes (CQAs) of these products. Herein, we provide an overview of the current state of analytics enabling measurement of CQAs such as capsid and vector identities, product titer, transduction efficiency, impurity clearance etc. We highlight orthogonal methods and discuss the advantages and limitations of these techniques while evaluating their adaptation as process analytical technologies. Finally, we identify gaps and propose opportunities in enabling existing technologies for real-time monitoring from hardware, software, and data analysis viewpoints for technology development within viral vector biomanufacturing.
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Affiliation(s)
- Sobhana A Sripada
- Department of Chemical and Biomolecular Engineering, North Carolina State University, 911 Partners Way, Raleigh, NC, 27695, USA
| | - Mahshid Hosseini
- Joint Department of Biomedical Engineering, North Carolina State University, and University of North Carolina, Chapel Hill, 911 Oval Dr., Raleigh, NC 27695, USA
| | - Srivatsan Ramesh
- Department of Chemical and Biomolecular Engineering, North Carolina State University, 911 Partners Way, Raleigh, NC, 27695, USA
| | - Junhyeong Wang
- Joint Department of Biomedical Engineering, North Carolina State University, and University of North Carolina, Chapel Hill, 911 Oval Dr., Raleigh, NC 27695, USA
| | - Kimberly Ritola
- North Carolina Viral Vector Initiative in Research and Learning (NC-VVIRAL), North Carolina State University, 890 Oval Dr, Raleigh, NC 27695, USA; Neuroscience Center, Brain Initiative Neurotools Vector Core, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Stefano Menegatti
- Department of Chemical and Biomolecular Engineering, North Carolina State University, 911 Partners Way, Raleigh, NC, 27695, USA; North Carolina Viral Vector Initiative in Research and Learning (NC-VVIRAL), North Carolina State University, 890 Oval Dr, Raleigh, NC 27695, USA; Biomanufacturing Training and Education Center, North Carolina State University, 890 Main Campus Dr, Raleigh, NC 27695, USA.
| | - Michael A Daniele
- Joint Department of Biomedical Engineering, North Carolina State University, and University of North Carolina, Chapel Hill, 911 Oval Dr., Raleigh, NC 27695, USA; North Carolina Viral Vector Initiative in Research and Learning (NC-VVIRAL), North Carolina State University, 890 Oval Dr, Raleigh, NC 27695, USA; Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Dr, Raleigh, NC 27695, USA.
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Xu X, Farnós O, Paes BCMF, Nesdoly S, Kamen AA. Multivariate data analysis on multisensor measurement for inline process monitoring of adenovirus production in HEK293 cells. Biotechnol Bioeng 2024; 121:2175-2192. [PMID: 38613199 DOI: 10.1002/bit.28712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/31/2024] [Accepted: 04/01/2024] [Indexed: 04/14/2024]
Abstract
In the era of Biopharma 4.0, process digitalization fundamentally requires accurate and timely monitoring of critical process parameters (CPPs) and quality attributes. Bioreactor systems are equipped with a variety of sensors to ensure process robustness and product quality. However, during the biphasic production of viral vectors or replication-competent viruses for gene and cell therapies and vaccination, current monitoring techniques relying on a single working sensor can be affected by the physiological state change of the cells due to infection/transduction/transfection step required to initiate production. To address this limitation, a multisensor (MS) monitoring system, which includes dual-wavelength fluorescence spectroscopy, dielectric signals, and a set of CPPs, such as oxygen uptake rate and pH control outputs, was employed to monitor the upstream process of adenovirus production in HEK293 cells in bioreactor. This system successfully identified characteristic responses to infection by comparing variations in these signals, and the correlation between signals and target critical variables was analyzed mechanistically and statistically. The predictive performance of several target CPPs using different multivariate data analysis (MVDA) methods on data from a single sensor/source or fused from multiple sensors were compared. An MS regression model can accurately predict viable cell density with a relative root mean squared error (rRMSE) as low as 8.3% regardless of the changes occurring over the infection phase. This is a significant improvement over the 12% rRMSE achieved with models based on a single source. The MS models also provide the best predictions for glucose, glutamine, lactate, and ammonium. These results demonstrate the potential of using MVDA on MS systems as a real-time monitoring approach for biphasic bioproduction processes. Yet, models based solely on the multiplicity and timing of infection outperformed both single-sensor and MS models, emphasizing the need for a deeper mechanistic understanding in virus production prediction.
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Affiliation(s)
- Xingge Xu
- Department of Bioengineering, McGill University, Montreal, Canada
| | - Omar Farnós
- Department of Bioengineering, McGill University, Montreal, Canada
| | | | - Sean Nesdoly
- Department of Bioengineering, McGill University, Montreal, Canada
| | - Amine A Kamen
- Department of Bioengineering, McGill University, Montreal, Canada
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Nie J, Ren H, Sun Y, Li Y, Zhang Y, Bai Z. Application of Multivariate Data Analysis on Historical Recombinant Adenovirus Zoster Vaccine Production Data for Upstream Process Improvements. J Pharm Sci 2024; 113:1168-1176. [PMID: 38447668 DOI: 10.1016/j.xphs.2024.02.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 03/08/2024]
Abstract
In recent years, multivariate data analysis (MVDA) has been widely used for process characterization and fault diagnosis in the biopharmaceutical industry. This study aims to investigate the feasibility of using MVDA for the development and scale-up of a perfusion process for HEK293 cell-based recombinant adenovirus zoster vaccine (Ad-HER) production. The Principal Component Analysis (PCA) results suggested comparable performance among the ATF, PATFP, and BFP perfusion systems in benchtop-scale stirred-tank bioreactor (STR). Then a Batch Evolution Model (BEM) was built using representative data from 10 L STR with a BFP system to assess the Ad-HER perfusion process performance at pilot-scale bioreactor (50 L STR and 50 L wave bioreactor). Furthermore, another BEM model and Batch Level Model (BLM) were built to monitor process parameters over time and predict the final adenovirus titer in 50 L wave bioreactor. The loading plot revealed that lactate dehydrogenase activity, viable cell diameter, and base-added during the virus production phase could be used as preliminary indicators of adenovirus yield. Finally, an adenovirus titer of 2.0±0.3×1010 IFU/mL was achieved in the 50 L wave bioreactor with BFP system, highlighting the robustness of the Ad-HER perfusion process at pilot-scale. Overall, this study emphasizes the effectiveness of MVDA as a tool for advancing the understanding of recombinant adenovirus vaccine perfusion production process development and scale-up.
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Affiliation(s)
- Jianqi Nie
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Life Sciences and Health Engineering, Jiangnan University, Wuxi 214122, China
| | - He Ren
- National Engineering Research Center of Cereal Fermentation and Food Biomanufacturing, Jiangnan University, Wuxi 214122, China
| | - Yang Sun
- School of Life Sciences, Henan University, Kaifeng 475004, China
| | - Ye Li
- National Engineering Research Center of Cereal Fermentation and Food Biomanufacturing, Jiangnan University, Wuxi 214122, China
| | - Yan Zhang
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Life Sciences and Health Engineering, Jiangnan University, Wuxi 214122, China.
| | - Zhonghu Bai
- National Engineering Research Center of Cereal Fermentation and Food Biomanufacturing, Jiangnan University, Wuxi 214122, China; The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi 214122, China; Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, Wuxi 214122, China.
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Jagtap GA, Badge A, Kohale MG, Wankhade RS. The Role of the Biosafety Cabinet in Preventing Infection in the Clinical Laboratory. Cureus 2023; 15:e51309. [PMID: 38288229 PMCID: PMC10823295 DOI: 10.7759/cureus.51309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/29/2023] [Indexed: 01/31/2024] Open
Abstract
Clinical laboratories are essential in healthcare to better diagnose, treat, and track medical diseases. However, handling infectious organisms and possibly infectious materials in these laboratories puts the safety of laboratory workers and the general public at risk. By controlling the distribution of infectious substances and stopping the spread of diseases, biosafety cabinets (BSCs) have become crucial tools in guaranteeing laboratory safety. The prevention of infections is most important in medical and laboratory settings. In clinical laboratories, biological and infectious agents are handled, posing threats to healthcare workers and the general public. To avoid infections, proper training of the BSC is essential. Laboratory employees are instructed in aseptic procedures, proper hand posture, and efficient personal protection when working in the cabinet. These instructions decrease the chance of contaminating the surrounding area. Additionally, user ergonomics are taken into account while designing BSC, reducing operator fatigue, and guaranteeing that staff can execute tasks precisely for extended periods. This review highlights the importance of biosafety cabinets in maintaining a secure laboratory environment and explains their crucial function in infection control.
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Affiliation(s)
- Gaurav A Jagtap
- Pathology, School of Allied Health Sciences, Datta Meghe Institute of Higher Education and Research, Nagpur, IND
| | - Ankit Badge
- Microbiology, Datta Meghe Medical College, Datta Meghe Institute of Higher Education and Research, Nagpur, IND
| | - Mangesh G Kohale
- Pathology, Datta Meghe Medical College, Datta Meghe Institute of Higher Education and Research, Nagpur, IND
| | - Rashmi S Wankhade
- Pathology, Datta Meghe Medical College, Datta Meghe Institute of Higher Education and Research, Nagpur, IND
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Fu Q, Polanco A, Lee YS, Yoon S. Critical challenges and advances in recombinant adeno-associated virus (rAAV) biomanufacturing. Biotechnol Bioeng 2023; 120:2601-2621. [PMID: 37126355 DOI: 10.1002/bit.28412] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/27/2023] [Accepted: 04/19/2023] [Indexed: 05/02/2023]
Abstract
Gene therapy is a promising therapeutic approach for genetic and acquired diseases nowadays. Among DNA delivery vectors, recombinant adeno-associated virus (rAAV) is one of the most effective and safest vectors used in commercial drugs and clinical trials. However, the current yield of rAAV biomanufacturing lags behind the necessary dosages for clinical and commercial use, which embodies a concentrated reflection of low productivity of rAAV from host cells, difficult scalability of the rAAV-producing bioprocess, and high levels of impurities materialized during production. Those issues directly impact the price of gene therapy medicine in the market, limiting most patients' access to gene therapy. In this context, the current practices and several critical challenges associated with rAAV gene therapy bioprocesses are reviewed, followed by a discussion of recent advances in rAAV-mediated gene therapy and other therapeutic biological fields that could improve biomanufacturing if these advances are integrated effectively into the current systems. This review aims to provide the current state-of-the-art technology and perspectives to enhance the productivity of rAAV while reducing impurities during production of rAAV.
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Affiliation(s)
- Qiang Fu
- Department of Biomedical Engineering and Biotechnology, The University of Massachusetts Lowell, Lowell, Massachusetts, USA
| | - Ashli Polanco
- Department of Chemical Engineering, The University of Massachusetts Lowell, Lowell, Massachusetts, USA
| | - Yong Suk Lee
- Department of Pharmaceutical Sciences, The University of Massachusetts Lowell, Lowell, Massachusetts, USA
| | - Seongkyu Yoon
- Department of Chemical Engineering, The University of Massachusetts Lowell, Lowell, Massachusetts, USA
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Iglesias CF, Ristovski M, Bolic M, Cuperlovic-Culf M. rAAV Manufacturing: The Challenges of Soft Sensing during Upstream Processing. Bioengineering (Basel) 2023; 10:bioengineering10020229. [PMID: 36829723 PMCID: PMC9951952 DOI: 10.3390/bioengineering10020229] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/31/2023] [Accepted: 02/02/2023] [Indexed: 02/11/2023] Open
Abstract
Recombinant adeno-associated virus (rAAV) is the most effective viral vector technology for directly translating the genomic revolution into medicinal therapies. However, the manufacturing of rAAV viral vectors remains challenging in the upstream processing with low rAAV yield in large-scale production and high cost, limiting the generalization of rAAV-based treatments. This situation can be improved by real-time monitoring of critical process parameters (CPP) that affect critical quality attributes (CQA). To achieve this aim, soft sensing combined with predictive modeling is an important strategy that can be used for optimizing the upstream process of rAAV production by monitoring critical process variables in real time. However, the development of soft sensors for rAAV production as a fast and low-cost monitoring approach is not an easy task. This review article describes four challenges and critically discusses the possible solutions that can enable the application of soft sensors for rAAV production monitoring. The challenges from a data scientist's perspective are (i) a predictor variable (soft-sensor inputs) set without AAV viral titer, (ii) multi-step forecasting, (iii) multiple process phases, and (iv) soft-sensor development composed of the mechanistic model.
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Affiliation(s)
| | - Milica Ristovski
- Faculty of Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Miodrag Bolic
- Faculty of Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Miroslava Cuperlovic-Culf
- Digital Technologies Research Center, National Research Council, Ottawa, ON K1A 0R6, Canada
- Department of Biochemistry, Microbiology, and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
- Correspondence:
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A Flexible Data Evaluation System for Improving the Quality and Efficiency of Laboratory Analysis and Testing. INFORMATION 2022. [DOI: 10.3390/info13090424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In a chemical analysis laboratory, sample detection via most analytical devices obtains raw data and processes it to validate data reports, including raw data filtering, editing, effectiveness evaluation, error correction, etc. This process is usually carried out manually by analysts. When the sample detection volume is large, the data processing involved becomes time-consuming and laborious, and manual errors may be introduced. In addition, analytical laboratories typically use a variety of analytical devices with different measurement principles, leading to the use of various heterogeneous control software systems from different vendors with different export data formats. Different formats introduce difficulties to laboratory automation. This paper proposes a modular data evaluation system that uses a global unified management and maintenance mode that can automatically filter data, evaluate quality, generate valid reports, and distribute reports. This modular software design concept allows the proposed system to be applied to different analytical devices; its integration into existing laboratory information management systems (LIMS) could maximise automation and improve the analysis and testing quality and efficiency in a chemical analysis laboratory, while meeting the analysis and testing requirements.
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Emerson J, Glassey J. Bioprocess monitoring and control: challenges in cell and gene therapy. Curr Opin Chem Eng 2021. [DOI: 10.1016/j.coche.2021.100722] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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