Chromatography bioseparation technologies and in-silico modelings for continuous production of biotherapeutics

Behere, Ketki; Yoon, Seongkyu

doi:10.1016/j.chroma.2020.461376

Cited by 17 publications

(11 citation statements)

References 93 publications

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Section: Discussionmentioning

confidence: 99%

“…Ultimately, combining individual chromatography models into models of multi-column chromatography processes will require an adaptation of the modeling approaches to handle the increased complexity, higher variability in experimental outcomes and therefore the additional experimental effort needed to generate suitable datasets for model validation ( Behere and Yoon 2020 ; Guo et al, 2020 ). Similarly, the computational effort will increase for the modeling of more than one column due to a combinatorial explosion ( Behere and Yoon 2020 ; Guo et al, 2020 ). All the more important will it be to establish standardized methodologies for model quality assessment that could form the basis for a good modeling practice (GMoP) complementing other GxP guidelines in the context of biopharmaceutical production ( Rischawy et al, 2019 ; Roush et al, 2020 ; Saleh et al, 2021b ; Rajamanickam et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

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The use of predictive models to develop chromatography-based purification processes

Bernau

Knödler

Emonts

et al. 2022

Front. Bioeng. Biotechnol.

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Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The use of predictive models to develop chromatography-based purification processes

Bernau

Knödler

Emonts

et al. 2022

Front. Bioeng. Biotechnol.

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“…Thus, the design and control of chromatography operations, as well as predicting the efficiency and yield of each column, are important for the development of continuous chromatography and its integration with upstream processes. 100 Mechanistic models, such as transportdispersive models and general rate models, have been widely used to simulate fluid diffusion and binding kinetics in chromatography processing. 75,76,82,[101][102][103] To simulate MCC, recent studies have integrated mechanistic models with column scheduling and interconnection nodes.…”

Section: Improvement Of Single Unit Operationmentioning

confidence: 99%

Recent advances in integrated process analytical techniques, modeling, and control strategies to enable continuous biomanufacturing of monoclonal antibodies

Chopda

Gyorgypal

et al. 2021

J of Chemical Tech & Biotech

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Continuous bioprocessing is significantly changing the biological drugs (or biologics) manufacturing landscape by potentially improving product quality, process stability, and overall profitability, as was similarly seen during the adoption of advanced manufacturing processes for small molecule drugs in the past decade. However, the implementation of continuous manufacturing for biological processes producing protein-based drug molecules, such as monoclonal antibodies (mAbs), is facing several new hurdles. The barriers to continuous bioprocessing can be overcome through improved process understanding via better predictive capabilities enabled by hybrid modeling that can also lead to robust process control. This review article summarizes the recent advances and ongoing obstacles faced during the use of advanced process analytical technologies (PAT), process modeling, and control strategies to enable continuous manufacturing of mAbs. In addition, this review also discusses the process strategies and future directions of advanced continuous manufacturing approaches that have been adapted by other industries and that could be implemented for mAbs production soon.

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“…The switch from batch to continuous chromatography has been predominantly carried out using counter-current multicolumn chromatography. 4 Simulated moving bed (SMB) chromatography is operated with two or more columns through which the mobile phase is flowing continuously while the solid phase flow is simulated by periodically shifting the columns opposite to the fluid phase. [5][6][7] SMB improves the utilization of the stationary phase by achieving loadings much closer to the static (maximum) binding capacity of the resin in comparison to batch chromatography and reduces column volumethereby adding to the intensification effect.…”

Section: Systems For Continuous Processing Using Beaded Adsorbentsmentioning

confidence: 99%

Perspectives on adsorption technology as an effective strategy for continuous downstream bioprocessing

Schneider

Herlevi

Guo

et al. 2021

J of Chemical Tech & Biotech

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The biological industry, but also biorefining platforms in the context of the circular economy, have been fertile terrains for the development of a palette of novel products of increasing structural diversity and fields of application. To mention only a few of the more complex bioproducts, we can consider monoclonal antibodies, plasmid DNA, virus‐like particles and exosomes. Of course, some products of industrial relevance are much simpler in nature. Irrespective of the product class and field of application, a shift from batch processing to continuous manufacturing is currently happening. This is due to the fact that operating in the continuous mode can result in process intensification, and therefore increased productivity with lower environmental impact can be realized. Some biological production schemes, e.g. those based on perfusion cultures, are well known in the pharmaceutical industry. Likewise, continuous fermentation is now utilized to produce ethanol from biomass. In many cases, continuous downstream operations are desired but difficult to implement; there is a pressing need to better understand the available options for product recovery and purification. Some traditional methods require re‐evaluation in modern contexts and some others, of experimental nature, require further improvement before actual implementation. In this article, we present an overview of the most promising methods that would allow for robust downstream bioprocessing options in the near future – with a focus on adsorption technologies. © 2021 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).

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Chromatography bioseparation technologies and in-silico modelings for continuous production of biotherapeutics

Cited by 17 publications

References 93 publications

The use of predictive models to develop chromatography-based purification processes

The use of predictive models to develop chromatography-based purification processes

Recent advances in integrated process analytical techniques, modeling, and control strategies to enable continuous biomanufacturing of monoclonal antibodies

Perspectives on adsorption technology as an effective strategy for continuous downstream bioprocessing

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