Domain antibody downstream process optimization: High‐throughput strategy and analytical methods

Welsh, John P.; Rauscher, Michael A.; Bao, Hongda; Meissner, Sandra; Han, InKwan; Linden, Thomas; Pollard, Jennifer M.

doi:10.1002/elsc.201400255

Cited by 9 publications

(7 citation statements)

References 18 publications

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“…However, human involvement was still needed in most steps, for example, in designing the experimental plan, in programming and initiating the liquid handling unit, in data treatment obtained from the plate reader, as well as in modification the plan of experiments for the next round. Such a strategy is in accordance with previously published automated HT platforms for bioprocess development [18,19]. Further extension of such an automated flow can be envisioned by a full closed-loop system as recently published by Wu and Zhou [18].…”

Section: Discussionsupporting

confidence: 71%

Design of experiments‐based high‐throughput strategy for development and optimization of efficient cell disruption protocols

Glauche

Pilarek

Bournazou

et al. 2016

Engineering in Life Sciences

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Efficient and reproducible cell lysis is a crucial step during downstream processing of intracellular products. The composition of an optimal lysis buffer should be chosen depending on the organism, its growth status, the applied detection methods, and even the target molecule. Especially for high‐throughput applications, where sample volumes are limited, the adaptation of a lysis buffer to the specific campaign is an urgent need. Here, we present a general design of experiments‐based strategy suitable for eight constituents and demonstrate the strength of this approach by the development of an efficient lysis buffer for Gram‐negative bacteria, which is applicable in a high‐throughput format in a short time. The concentrations of four lysis‐inducing chemical agents EDTA, lysozyme, Triton X‐100, and polymyxin B were optimized for maximal soluble protein concentration and ß‐galactosidase activity in a 96‐well format on a Microlab Star liquid handling platform under design of experiments methodology. The resulting lysis buffer showed the same performance as a commercially available lysis buffer. The developed protocol resulted in an optimized buffer within only three runs. The established procedure can be easily applied to adapt the lysis buffer to other strains and target molecules.

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Section: Discussionsupporting

confidence: 71%

Design of experiments‐based high‐throughput strategy for development and optimization of efficient cell disruption protocols

Glauche

Pilarek

Bournazou

et al. 2016

Engineering in Life Sciences

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“…The Highland Games competition draws upon a rich tradition of collaboration and benchmarking in the precompetitive advancement of industries, including the elucidation of CHO cell metabolism (Hefzi et al, 2016), the benchmarking of MHC Class II binding prediction methods (Andreatta et al, 2018), the characterization of the NISTmAb (Schiel & Turner, 2018), the A‐Mab QBD exercise (CMC Biotech Working Group, 2009), high‐throughput process development Olympiad 2014 (http://www.htpdmeetings.com; Welsh et al, 2016) the Industrial Fluid Properties Simulation Challenge (http://fluidproperties.org/), the long‐running CASP protein competitions of the Protein Structure Prediction Center (http://predictioncenter.org/casp13) and (in a different but increasingly relevant field) the Kaggle competition (http://www.kaggle.com) for development of data science tools. In all these diverse areas, competition and benchmarking have advanced the state‐of‐the‐art, especially when competitors generously share knowledge of best practices.…”

Section: Discussionmentioning

confidence: 99%

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences

Coffman

Marques

Orozco

et al. 2020

Biotech & Bioengineering

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Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first “Highland Games” competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development‐related properties of six antibodies from their amino acid sequences alone. Predictions included purification‐influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all‐prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in‐house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.

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“…Separations with three or more similar compounds in the feed are often complex and therefore typically require considerably more optimization than the initial mAb capture step. Examples of such process development efforts to achieve sufficient clearance from antibody aggregates are reported in the literature [1][2][3][4][5] ; examples of ternary separations involving aggregates as well as other product-related impurities are less frequent. [6][7][8][9] Other examples of ternary mixtures comprising non-mAb proteins, namely BSA, ovalbumin, cytochrome C, and ribonuclease A, are commonly employed to study model-based optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Hybrid optimization of preparative chromatography for a ternary monoclonal antibody mixture

Fischer

Kucia-Tran

Lewis

et al. 2019

Biotechnology Progress

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In the purification of monoclonal antibodies, ion‐exchange chromatography is typically used among the polishing steps to reduce the amount of product‐related impurities such as aggregates and fragments, whilst simultaneously reducing HCP, residual Protein A and potential toxins and viruses. When the product‐related impurities are difficult to separate from the products, the optimization of these chromatographic steps can be complex and laborious. In this paper, we optimize the polishing chromatography of a monoclonal antibody from a challenging ternary feed mixture by introducing a hybrid approach of the simplex method and a form of local optimization. To maximize the productivity of this preparative bind‐and‐elute cation‐exchange chromatography, wide ranges of the three critical operational parameters—column loading, the initial salt concentration, and gradient slope—had to be considered. The hybrid optimization approach is shown to be extremely effective in dealing with this complex separation that was subject to multiple constraints based on yield, purity, and product breakthrough. Furthermore, it enabled the generation of a large knowledge space that was subsequently used to study the sensitivity of the objective function. Increased design space understanding was gained through the application of Monte Carlo simulations. Hence, this work proposes a powerful hybrid optimization method, applied to an industrially relevant process development challenge. The properties of this approach and the results and insights gained, make it perfectly suited for the rapid development of biotechnological unit operations during early‐stage bioprocess development.

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Domain antibody downstream process optimization: High‐throughput strategy and analytical methods

Cited by 9 publications

References 18 publications

Design of experiments‐based high‐throughput strategy for development and optimization of efficient cell disruption protocols

Design of experiments‐based high‐throughput strategy for development and optimization of efficient cell disruption protocols

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences

Hybrid optimization of preparative chromatography for a ternary monoclonal antibody mixture

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