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Graf T, Naumann L, Bonnington L, Heckel J, Spensberger B, Klein S, Brey C, Nachtigall R, Mroz M, Hogg TV, McHardy C, Martinez A, Braaz R, Leiss M. Expediting online liquid chromatography for real-time monitoring of product attributes to advance process analytical technology in downstream processing of biopharmaceuticals. J Chromatogr A 2024; 1729:465013. [PMID: 38824753 DOI: 10.1016/j.chroma.2024.465013] [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: 03/18/2024] [Revised: 05/16/2024] [Accepted: 05/20/2024] [Indexed: 06/04/2024]
Abstract
The application of Process Analytical Technology (PAT) principles for manufacturing of biotherapeutics proffers the prospect of ensuring consistent product quality along with increased productivity as well as substantial cost and time savings. Although this paradigm shift from a traditional, rather rigid manufacturing model to a more scientific, risk-based approach has been advocated by health authorities for almost two decades, the practical implementation of PAT in the biopharmaceutical industry is still limited by the lack of fit-for-purpose analytical methods. In this regard, most of the proposed spectroscopic techniques are sufficiently fast but exhibit deficiencies in terms of selectivity and sensitivity, while well-established offline methods, such as (ultra-)high-performance liquid chromatography, are generally considered as too slow for this task. To address these reservations, we introduce here a novel online Liquid Chromatography (LC) setup that was specifically designed to enable real-time monitoring of critical product quality attributes during time-sensitive purification operations in downstream processing. Using this online LC solution in combination with fast, purpose-built analytical methods, sampling cycle times between 1.30 and 2.35 min were achieved, without compromising on the ability to resolve and quantify the product variants of interest. The capabilities of our approach are ultimately assessed in three case studies, involving various biotherapeutic modalities, downstream processes and analytical chromatographic separation modes. Altogether, our results highlight the expansive opportunities of online LC based applications to serve as a PAT tool for biopharmaceutical manufacturing.
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Affiliation(s)
- Tobias Graf
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Lukas Naumann
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Lea Bonnington
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Jakob Heckel
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Bernhard Spensberger
- Pharma Research and Early Development (pRED), Roche Innovation Center Munich, Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany
| | - Sascha Klein
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Christoph Brey
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Ronnie Nachtigall
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Maximilian Mroz
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Thomas Vagn Hogg
- Pharma Research and Early Development (pRED), Roche Innovation Center Munich, Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany
| | - Christopher McHardy
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Andrés Martinez
- Gene Therapy Technical Development, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Reinhard Braaz
- Pharma Technical Development Clinical Supply Center, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Michael Leiss
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany.
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Javidanbardan A, Messerian KO, Zydney AL. Membrane technology for the purification of RNA and DNA therapeutics. Trends Biotechnol 2024; 42:714-727. [PMID: 38212210 DOI: 10.1016/j.tibtech.2023.11.016] [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: 08/29/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 01/13/2024]
Abstract
Nucleic acid therapeutics have the potential to revolutionize the biopharmaceutical industry, providing highly effective vaccines and novel treatments for cancers and genetic disorders. The successful commercialization of these therapeutics will require development of manufacturing strategies specifically tailored to the purification of nucleic acids. Membrane technologies already play a critical role in the downstream processing of nucleic acid therapeutics, ranging from clarification to concentration to selective purification. This review provides an overview of how membrane systems are currently used for nucleic acid purification, while highlighting areas of future need and opportunity, including adoption of membranes in continuous bioprocessing.
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Affiliation(s)
- Amin Javidanbardan
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Kevork Oliver Messerian
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Andrew L Zydney
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
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3
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Shi C, Chen XJ, Zhong XZ, Yang Y, Lin DQ, Chen R. Realization of digital twin for dynamic control toward sample variation of ion exchange chromatography in antibody separation. Biotechnol Bioeng 2024; 121:1702-1715. [PMID: 38230585 DOI: 10.1002/bit.28660] [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: 10/24/2023] [Revised: 12/26/2023] [Accepted: 01/05/2024] [Indexed: 01/18/2024]
Abstract
Digital twin (DT) is a virtual and digital representation of physical objects or processes. In this paper, this concept is applied to dynamic control of the collection window in the ion exchange chromatography (IEC) toward sample variations. A possible structure of a feedforward model-based control DT system was proposed. Initially, a precise IEC mechanistic model was established through experiments, model fitting, and validation. The average root mean square error (RMSE) of fitting and validation was 8.1% and 7.4%, respectively. Then a model-based gradient optimization was performed, resulting in a 70.0% yield with a remarkable 11.2% increase. Subsequently, the DT was established by systematically integrating the model, chromatography system, online high-performance liquid chromatography, and a server computer. The DT was validated under varying load conditions. The results demonstrated that the DT could offer an accurate control with acidic variants proportion and yield difference of less than 2% compared to the offline analysis. The embedding mechanistic model also showed a positive predictive performance with an average RMSE of 11.7% during the DT test under >10% sample variation. Practical scenario tests indicated that tightening the control target could further enhance the DT robustness, achieving over 98% success rate with an average yield of 72.7%. The results demonstrated that the constructed DT could accurately mimic real-world situations and perform an automated and flexible pooling in IEC. Additionally, a detailed methodology for applying DT was summarized.
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Affiliation(s)
- Ce Shi
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Xu-Jun Chen
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Xue-Zhao Zhong
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Yan Yang
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Dong-Qiang Lin
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Ran Chen
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
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Rathore AS, Sarin D. What should next-generation analytical platforms for biopharmaceutical production look like? Trends Biotechnol 2024; 42:282-292. [PMID: 37775418 DOI: 10.1016/j.tibtech.2023.08.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/29/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Biotherapeutic products, particularly complex products such as monoclonal antibodies (mAbs), have as many as 20-30 critical quality attributes (CQAs), thereby requiring a collection of orthogonal, high-resolution analytical tools for characterization and making characterization a resource-intensive task. As discussed in this Opinion, the need to reduce the cost of developing biotherapeutic products and the need to adopt Industry 4.0 and eventually Industry 5.0 paradigms are driving a reappraisal of existing analytical platforms. Next-generation platforms will have reduced offline testing, renewed focus on online testing and real-time monitoring, multiattribute monitoring, and extensive use of advanced data analytics and automation. They will be more complex, more sensitive, resource lean, and more responsive compared with existing platforms.
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Affiliation(s)
- Anurag S Rathore
- Department of Chemical Engineering, Indian Institute of Technology Delhi, Delhi, India.
| | - Deepika Sarin
- Department of Chemical Engineering, Indian Institute of Technology Delhi, Delhi, India
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Chen H, Tian Y, Zhang S, Wang X, Qu H. Image processing-based online analysis and feedback control system for droplet dripping process. Int J Pharm 2024; 651:123736. [PMID: 38142872 DOI: 10.1016/j.ijpharm.2023.123736] [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: 09/26/2023] [Revised: 12/01/2023] [Accepted: 12/21/2023] [Indexed: 12/26/2023]
Abstract
Droplets find wide application across diverse industries, where maintaining their quality is paramount. Precise control over the substance content within droplets demands non-destructive and online analysis techniques, such as Process Analytical Technology (PAT), often integrated with control strategies. In this context, the present study focuses on the example of controlling droplet quality during the dripping process of pills. Leveraging the dripping and image acquisition systems established in previous research, a novel feedback control system centered on image processing was devised for the quality control of dripping pills. The system was developed and its efficacy was assessed, yielding satisfactory outcomes. The proposed system facilitates real-time monitoring of pill weight through the analysis of droplet images during the dripping process, thereby offering real-time feedback control of pill weight. Importantly, this system holds potential for broader applications beyond the scope of this study.
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Affiliation(s)
- Hang Chen
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Ying Tian
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Sheng Zhang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Xiaoping Wang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Haibin Qu
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
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Desai PG, Garidel P, Gbormittah FO, Kamen DE, Mills BJ, Narasimhan CN, Singh S, Stokes ESE, Walsh ER. An Intercompany Perspective on Practical Experiences of Predicting, Optimizing and Analyzing High Concentration Biologic Therapeutic Formulations. J Pharm Sci 2023; 112:359-369. [PMID: 36442683 DOI: 10.1016/j.xphs.2022.11.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/18/2022] [Accepted: 11/18/2022] [Indexed: 11/27/2022]
Abstract
Developing high-dose biologic drugs for subcutaneous injection often requires high-concentration formulations and optimizing viscosity, solubility, and stability while overcoming analytical, manufacturing, and administration challenges. To understand industry approaches for developing high-concentration formulations, the Formulation Workstream of the BioPhorum Development Group, an industry-wide consortium, conducted an inter-company collaborative exercise which included several surveys. This collaboration provided an industry perspective, experience, and insight into the practicalities for developing high-concentration biologics. To understand solubility and viscosity, companies desire predictive tools, but experience indicates that these are not reliable and experimental strategies are best. Similarly, most companies prefer accelerated and stress stability studies to in-silico or biophysical-based prediction methods to assess aggregation. In addition, optimization of primary container-closure and devices are pursued to mitigate challenges associated with high viscosity of the formulation. Formulation strategies including excipient selection and application of studies at low concentration to high-concentration formulations are reported. Finally, analytical approaches to high concentration formulations are presented. The survey suggests that although prediction of viscosity, solubility, and long-term stability is desirable, the outcome can be inconsistent and molecule dependent. Significant experimental studies are required to confirm robust product definition as modeling at low protein concentrations will not necessarily extrapolate to high concentration formulations.
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Affiliation(s)
- Preeti G Desai
- Bristol Myers Squibb, Sterile Product Development, 556 Morris Avenue, Summit, NJ 07901, USA
| | - Patrick Garidel
- Boehringer Ingelheim Pharma GmbH Co KG, Innovation Unit, PDB-TIP, 88397 Biberach an der Riss, Germany
| | - Francisca O Gbormittah
- GlaxoSmithKline, Strategic External Development, 1000 Winter Street North, Waltham, MA 02451, USA
| | - Douglas E Kamen
- Regeneron Pharmaceuticals Inc., Formulation Development, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Brittney J Mills
- AbbVie, NBE Drug Product Development, 1 N Waukegan Road, North Chicago, IL 60064, USA
| | | | - Shubhadra Singh
- GlaxoSmithKline R&D, Biopharmaceutical Product Sciences, Collegeville, PA 19426, USA
| | - Elaine S E Stokes
- BioPhorum, The Gridiron Building, 1 Pancras Square, London N1C 4AG UK.
| | - Erika R Walsh
- Merck & Co., Inc., Sterile and Specialty Products, Rahway, NJ, USA
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Rolinger L, Hubbuch J, Rüdt M. Monitoring of ultra- and diafiltration processes by Kalman-filtered Raman measurements. Anal Bioanal Chem 2023; 415:841-854. [PMID: 36651972 PMCID: PMC9883314 DOI: 10.1007/s00216-022-04477-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 11/24/2022] [Accepted: 12/07/2022] [Indexed: 01/19/2023]
Abstract
Monitoring the protein concentration and buffer composition during the Ultrafiltration/Diafiltration (UF/DF) step enables the further automation of biopharmaceutical production and supports Real-time Release Testing (RTRT). Previously, in-line Ultraviolet (UV) and Infrared (IR) measurements have been used to successfully monitor the protein concentration over a large range. The progress of the diafiltration step has been monitored with density measurements and Infrared Spectroscopy (IR). Raman spectroscopy is capable of measuring both the protein and excipient concentration while being more robust and suitable for production measurements in comparison to Infrared Spectroscopy (IR). Regardless of the spectroscopic sensor used, the low concentration of excipients poses a challenge for the sensors. By combining sensor measurements with a semi-mechanistic model through an Extended Kalman Filter (EKF), the sensitivity to determine the progress of the diafiltration can be improved. In this study, Raman measurements are combined with an EKF for three case studies. The advantages of Kalman-filtered Raman measurements for excipient monitoring are shown in comparison to density measurements. Furthermore, Raman measurements showed a higher measurement speed in comparison to Variable Pathlength (VP) UV measurement at the trade-off of a slightly worse prediction accuracy for the protein concentration. However, the Raman-based protein concentration measurements relied mostly on an increase in the background signal during the process and not on proteinaceous features, which could pose a challenge due to the potential influence of batch variability on the background signal. Overall, the combination of Raman spectroscopy and EKF is a promising tool for monitoring the UF/DF step and enables process automation by using adaptive process control.
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Affiliation(s)
- Laura Rolinger
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Hoffmann-La Roche AG, Basel, Switzerland
| | - Jürgen Hubbuch
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Matthias Rüdt
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
- Haute Ecole d'Ingénierie (HEI), HES-SO Valais-Wallis, Rue de l'industrie 19, Sion, Switzerland.
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Chen R, Chen XJ, Shi C, Jiao B, Shi Y, Yao B, Lin DQ, Gong W, Hsu S. Converting a mAb downstream process from batch to continuous using process modeling and process analytical technology. Biotechnol J 2022; 17:e2100351. [PMID: 35908168 DOI: 10.1002/biot.202100351] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 07/28/2022] [Accepted: 07/28/2022] [Indexed: 11/06/2022]
Abstract
The biopharmaceutical market is driving the revolution from traditional batch processes to continuous manufacturing for higher productivity and lower costs. In this work, a batch mAb downstream process has been converted into an integrated continuous process with the combination of multiple techniques. For process intensification, two batch mode unit operations (protein A capture chromatography, ultrafiltration/diafiltration) are converted into continuous ones; For continuity, surge tanks were used between adjacent steps, and level signals were used to trigger process start or stop, forming a holistic continuous process. For process automation, manual operations (e.g., pH and conductivity adjustment) were changed into automatic operation and load mass was controlled with process analytical technology (PAT). A model-based simulation was applied to estimate the loading conditions for the continuous capture process, resulting in 21% resin capacity utilization and 28% productivity improvement as compared to the batch process. Automatic load mass control of cation exchange chromatography was achieved through a customized in-line protein quantity monitoring system, with a difference of less than 1.3% as compared to off-line analysis. Total process time was shortened from 4 days (batch process) to less than 24 hours using the continuous downstream process with the overall productivity of 23.8 g mAb /day for the bench-scale system. Comparable yield and quality data were obtained in three test runs, indicating a successful conversion from a batch process to a continuous process. The insight of this work could be a reference to other similar situations. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Ran Chen
- Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Xu-Jun Chen
- Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Ce Shi
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Biao Jiao
- Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Ye Shi
- Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Bin Yao
- Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Dong-Qiang Lin
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Wei Gong
- Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Simon Hsu
- Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
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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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