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Anupa A, Metya S, Mihooliya KN, Rathore AS. Development of continuous processing platform utilizing aqueous two-phase extraction for purification of monoclonal antibodies. J Chromatogr A 2024; 1715:464605. [PMID: 38150873 DOI: 10.1016/j.chroma.2023.464605] [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: 11/11/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 12/29/2023]
Abstract
Monoclonal antibody downstream processing typically entails chromatography-based purification processes beginning with Protein A chromatography, accounting for 50 % of the total manufacturing expense. Alternatives to protein A chromatography have been explored by several researchers. In this paper, aqueous two-phase extraction (ATPE) has been proposed for continuous processing of monoclonal antibodies (mAbs) as an alternative to the traditional protein A chromatography. The PEG-sulfate system has been employed for phase formation in ATPE, and the mAb is separated in the salt phase, while impurities like high molecular weight (HMW) and host cell proteins (HCPs) are separated in the PEG phase. Following ATPE of clarified cell culture harvest, yield of ≥ 80 % and purity of ≥ 97 % were achieved in the salt phase. Considerable (28 %) reduction in consumable cost has been estimated when comparing the proposed platform to the traditional protein A based platform. The outcomes demonstrate that ATPE can be a potentially effective substitute for the traditional Protein A chromatography for purification of mAbs. The proposed platform offers easy implementation, delivers comparative results, and offers significantly better economics for manufacturing mAb-based biotherapeutics.
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Affiliation(s)
- Anupa Anupa
- School of Interdisciplinary Research, Indian Institute of Technology Delhi, New Delhi, India
| | - Subhankar Metya
- School of Interdisciplinary Research, Indian Institute of Technology Delhi, New Delhi, India
| | - Kanti N Mihooliya
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Anurag S Rathore
- School of Interdisciplinary Research, Indian Institute of Technology Delhi, New Delhi, India; Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
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Drobnjakovic M, Hart R, Kulvatunyou BS, Ivezic N, Srinivasan V. Current challenges and recent advances on the path towards continuous biomanufacturing. Biotechnol Prog 2023; 39:e3378. [PMID: 37493037 DOI: 10.1002/btpr.3378] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/13/2023] [Accepted: 06/21/2023] [Indexed: 07/27/2023]
Abstract
Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.
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Affiliation(s)
- Milos Drobnjakovic
- Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Roger Hart
- National Institute for Innovation in Manufacturing Biopharmaceuticals, Newark, New Jersey, USA
| | - Boonserm Serm Kulvatunyou
- Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Nenad Ivezic
- Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Vijay Srinivasan
- Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
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Rathore AS, Nikita S, Thakur G, Mishra S. Artificial intelligence and machine learning applications in biopharmaceutical manufacturing. Trends Biotechnol 2023; 41:497-510. [PMID: 36117026 DOI: 10.1016/j.tibtech.2022.08.007] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/08/2022] [Accepted: 08/22/2022] [Indexed: 11/30/2022]
Abstract
Artificial intelligence and machine learning (AI-ML) offer vast potential in optimal design, monitoring, and control of biopharmaceutical manufacturing. The driving forces for adoption of AI-ML techniques include the growing global demand for biotherapeutics and the shift toward Industry 4.0, spurring the rise of integrated process platforms and continuous processes that require intelligent, automated supervision. This review summarizes AI-ML applications in biopharmaceutical manufacturing, with a focus on the most used AI-ML algorithms, including multivariate data analysis, artificial neural networks, and reinforcement learning. Perspectives on the future growth of AI-ML applications in the area and the challenges of implementing these techniques at manufacturing scale are also presented.
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Affiliation(s)
- Anurag S Rathore
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
| | - Saxena Nikita
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Garima Thakur
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Somesh Mishra
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
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Nitika N, Thakur G, Rathore AS. Continuous manufacturing of monoclonal antibodies: Dynamic control of multiple integrated polishing chromatography steps using BioSMB. J Chromatogr A 2023; 1690:463784. [PMID: 36640682 DOI: 10.1016/j.chroma.2023.463784] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/01/2023] [Accepted: 01/07/2023] [Indexed: 01/09/2023]
Abstract
We propose a strategy for automation and control of multi-step polishing chromatography in integrated continuous manufacturing of monoclonal antibodies. The strategy is demonstrated for a multi-step polishing process consisting of cation exchange chromatography in bind-and-elute mode followed by mixed-mode chromatography in flowthrough mode. A BioSMB system with a customized Python control layer is used for automation and scheduling of both the chromatography steps. Further, the BioSMB valve manifold is leveraged for in-line conditioning between the two steps, as tight control of pH and conductivity is essential when operating with multimodal resins because even slight fluctuations in load conditions adversely affect the chromatography performance. The pH and conductivity of the load to the multimodal chromatography columns is consistent, despite the elution gradient of the preceding cation exchange chromatography step. Inputs from the BioSMB pH and conductivity sensors are used for real-time control of the 7 pumps and 240 valves to achieve in-line conditioning inside the BioSMB manifold in a fully automated manner. This is confirmed by showcasing different elution strategies in cation exchange chromatography, including linear gradient, step gradient and process deviations like tubing leakage. In all the above cases, the model was able to maintain the pH and conductivity of multimodal chromatography load within the range of 6 ± 0.1 pH and 7 ± 0.3 mS/cm conductivity. The strategy eliminates the need for using multiple BioSMB units or integrating external pumps, valves, mixers, surge tanks, or sensors between the two steps as is currently the standard approach, thus offering a simple and robust structure for integrating multiple polishing chromatography steps in continuous downstream monoclonal antibody purification trains.
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Affiliation(s)
- Nitika Nitika
- Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
| | - Garima Thakur
- Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
| | - Anurag S Rathore
- Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.
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Rathore AS, Thakur G, Kateja N. Continuous integrated manufacturing for biopharmaceuticals: A new paradigm or an empty promise? Biotechnol Bioeng 2023; 120:333-351. [PMID: 36111450 DOI: 10.1002/bit.28235] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/09/2022] [Accepted: 09/11/2022] [Indexed: 01/13/2023]
Abstract
Continuous integrated bioprocessing has elicited considerable interest from the biopharma industry for the many purported benefits it promises. Today many major biopharma manufacturers around the world are engaged in the development of continuous process platforms for their products. In spite of great potential, the path toward continuous integrated bioprocessing remains unclear for the biologics industry due to legacy infrastructure, process integration challenges, vague regulatory guidelines, and a diverging focus toward novel therapies. In this article, we present a review and perspective on this topic. We explore the status of the implementation of continuous integrated bioprocessing among biopharmaceutical manufacturers. We also present some of the key hurdles that manufacturers are likely to face during this implementation. Finally, we hypothesize that the real impact of continuous manufacturing is likely to come when the cost of manufacturing is a substantial portion of the cost of product development, such as in the case of biosimilar manufacturing and emerging economies.
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Affiliation(s)
- Anurag S Rathore
- Department of Chemical Engineering, Indian Institute of Technology, New Delhi, India
| | - Garima Thakur
- Department of Chemical Engineering, Indian Institute of Technology, New Delhi, India
| | - Nikhil Kateja
- Department of Chemical Engineering, Indian Institute of Technology, New Delhi, India
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Matanguihan C, Wu P. Upstream continuous processing: recent advances in production of biopharmaceuticals and challenges in manufacturing. Curr Opin Biotechnol 2022; 78:102828. [PMID: 36332340 DOI: 10.1016/j.copbio.2022.102828] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 09/12/2022] [Accepted: 09/27/2022] [Indexed: 12/14/2022]
Abstract
Upstream continuous processing, or most commonly perfusion processing, for biopharmaceutical production, is emerging as a feasible and viable manufacturing approach. Development in production of recombinant therapeutic proteins as well as viral vectors, vaccines, and cell therapy products, has numerous research publications that came out in previous years. Recent research areas are in perfusion-operation strategies maximizing and controlling bioreactor cell density, adding feed solution designed to supplement basal medium feed stream, combining cell line engineering with bioreactor conditions such as hypoxia, and implementing online process monitoring of cell density by capacitance sensor and metabolites by Raman spectroscopy. Perfusion applications are not limited to production process alone but include other upstream areas where high cell density process is essential such as in cell bank preparation, N-1 seed bioreactor, and combination with intensified fed-batch production process. This review covers recent advances in continuous processing over the last two years for biopharmaceutical production.
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Affiliation(s)
- Cary Matanguihan
- Bayer U.S. LLC, Pharmaceuticals, Biologics Development, 800 Dwight Way, Berkeley, CA 94701, USA.
| | - Paul Wu
- Bayer U.S. LLC, Pharmaceuticals, Biologics Development, 800 Dwight Way, Berkeley, CA 94701, USA
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Thakur G, Bansode V, Rathore AS. Continuous manufacturing of monoclonal antibodies: Automated downstream control strategy for dynamic handling of titer variations. J Chromatogr A 2022; 1682:463496. [PMID: 36126561 DOI: 10.1016/j.chroma.2022.463496] [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: 08/04/2022] [Revised: 09/06/2022] [Accepted: 09/08/2022] [Indexed: 11/16/2022]
Abstract
Handling long-term dynamic variability in harvest titer is a critical challenge in continuous downstream manufacturing. This challenge is becoming increasingly important with the advent of high-titer clones and modern upstream perfusion processes where the titer can vary significantly across the course of a campaign. In this paper, we present a strategy for real-time, dynamic adjustment of the entire downstream train, including capture chromatography, viral inactivation, depth filtration, polishing chromatography, and single-pass formulation, to accommodate variations in titer from 1-7 g/L. The strategy was tested in real time in a continuous downstream purification process of 36 h duration with induced titer variations. The dynamic control strategy leverages real-time NIR-based concentration sensors in the harvest material to continuously track the titer, integrated with an in-house Python-based control system that operates a BioSMB for carrying out capture and polishing chromatography, as well as a series of pumps and solenoid valves for carrying out viral inactivation and formulation. A set of 9 different methods, corresponding to the different harvest titers have been coded onto the Python controller. The methods have a varying number of chromatography columns (3-6 for Protein A and 2-10 for CEX), designed to ensure proper scheduling and optimize productivity across the entire titer variation space. The approach allows for a wide range of titers to be processed on a single integrated setup without having to change equipment or to re-design each time. The strategy also overcomes a key unexplored challenge in continuous processing, namely hand-shaking the downstream train to upstream conditions with long-term titer variability while maintaining automated operation with high productivity and robustness.
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Affiliation(s)
- Garima Thakur
- Department of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India
| | - Vikrant Bansode
- Department of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India
| | - Anurag S Rathore
- Department of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India.
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Ding C, Ardeshna H, Gillespie C, Ierapetritou M. Process Design of a Fully Integrated Continuous Biopharmaceutical Process using Economic and Ecological Impact Assessment. Biotechnol Bioeng 2022; 119:3567-3583. [DOI: 10.1002/bit.28234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 08/31/2022] [Accepted: 09/11/2022] [Indexed: 11/06/2022]
Affiliation(s)
- Chaoying Ding
- Department of Chemical and Biomolecular EngineeringUniversity of DelawareNewarkDE19716US
| | - Hiren Ardeshna
- Manufacturing Science and Technology, Biopharm and Steriles, GlaxoSmithKlinePhiladelphiaPA19112US
| | | | - Marianthi Ierapetritou
- Department of Chemical and Biomolecular EngineeringUniversity of DelawareNewarkDE19716US
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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: 1.7] [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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Nikita S, Thakur G, Jesubalan NG, Kulkarni A, Yezhuvath VB, Rathore AS. AI-ML applications in bioprocessing: ML as an enabler of real time quality prediction in continuous manufacturing of mAbs. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2022.107896] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Thakur G, Masampally V, Kulkarni A, Rathore AS. Process Analytical Technology (PAT) Implementation for Membrane Operations in Continuous Manufacturing of mAbs: Model-Based Control of Single-Pass Tangential Flow Ultrafiltration. AAPS J 2022; 24:83. [DOI: 10.1208/s12248-022-00731-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 06/30/2022] [Indexed: 11/30/2022] Open
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Thakur G, Ghumade P, Rathore AS. Process analytical technology in continuous processing: Model-based real time control of pH between capture chromatography and viral inactivation for monoclonal antibody production. J Chromatogr A 2021; 1658:462614. [PMID: 34656843 DOI: 10.1016/j.chroma.2021.462614] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 08/25/2021] [Accepted: 10/05/2021] [Indexed: 11/16/2022]
Abstract
A real time mechanistic model-based control strategy is demonstrated for in-line pH adjustment post-capture chromatography and prior to viral inactivation for continuous processing of monoclonal antibodies. At this point in the process, tight control of pH is essential, as pH fluctuations above 3.5 can result in incomplete viral inactivation, while fluctuations below 3.5 can lead to significant aggregate formation. The present approach predicts the pH profile during the transition phase between chromatography wash and elution steps by modelling the process stream at the column outlet as a mixture of two independent buffer systems. Control of pH in this transition phase is a critical consideration in capture chromatography as a significant amount of mAb material is eluted at this time. The model inputs are buffer concentrations, flow rates, and theoretical pKa values, along with cleaning step conductivity profiles which are readily available from a typical process chromatography equipment. The utilization of the most recent cleaning cycle data as an input to the model allows sensitive calibration to the individual process at hand on a column-to-column basis. The model is able to accurately predict the pH profile throughout the elution, as well as calculate the flow rate of the acid (titrant) required at each time point to maintain the pH consistently at 3.5±0.2. The strategy is demonstrated for various buffers, columns, operating conditions, and process deviations in a three-column continuous process, and is a useful and simple approach for achieving robust control of pH at this critical point in the continuous train.
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Affiliation(s)
- Garima Thakur
- Department of Chemical Engineering, Indian Institute of Technology, 110016, Hauz Khas, India
| | - Pragati Ghumade
- Department of Chemical Engineering, Indian Institute of Technology, 110016, Hauz Khas, India
| | - Anurag S Rathore
- Department of Chemical Engineering, Indian Institute of Technology, 110016, Hauz Khas, India.
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