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高地运动会:一项从氨基酸序列预测单克隆抗体生物物理和药物特性的基准测试。

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

作者信息

Coffman Jonathan, Marques Bruno, Orozco Raquel, Aswath Minni, Mohammad Hasan, Zimmermann Eike, Khouri Joelle, Griesbach Jan, Izadi Saeed, Williams Ambrose, Sankar Kannan, Walters Benjamin, Lin Jasper, Hepbildikler Stefan, Schiel John, Welsh John, Ferreira Gisela, Delmar Jared, Mody Neil, Afdahl Christopher, Cui Tingting, Khalaf Rushd, Hanke Alexander, Pampel Lars, Parimal Siddharth, Hong Xuan, Patil Ujwal, Pollard Jennifer, Insaidoo Francis, Robinson Julie, Chandra Divya, Blanco Marco, Panchal Jainik, Soundararajan Soundara, Roush David, Tugcu Nihal, Cramer Steven, Haynes Charles, Willson Richard C

机构信息

AstraZeneca, Gaithersburg, Maryland.

Process Development, Century Therapeutics, Philadelphia, Pennsylvania.

出版信息

Biotechnol Bioeng. 2020 Jul;117(7):2100-2115. doi: 10.1002/bit.27349. Epub 2020 May 9.

Abstract

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.

摘要

生物制药产品和工艺开发尚未像小分子行业那样充分利用预测性计算建模。为了评估和推动该领域的进展,积极的合作竞争(竞争对手之间的互利合作)被成功用于激励工业科学家开发、共享和比较通常会保密的数据和方法。首届“高地运动会”竞赛于2018年10月在北卡罗来纳州阿什维尔举行的生物制品回收会议期间举行,目标是仅根据六种抗体的氨基酸序列对其与开发相关的特性进行基准测试和评估。预测内容包括影响纯化的特性,如等电点和蛋白A洗脱pH值,以及生物物理特性,如极高浓度下的稳定性和粘度。众多个人做出了重要贡献,包括同意提供抗体氨基酸序列和测试材料的公司、负责这些材料制备和实验表征的志愿者,以及试图仅从序列预测抗体特性的预测团队。确定并分享了最佳实践,明确了该领域在进行预测方面表现出色的领域,以及仍有大幅改进空间的领域。等电点和蛋白A洗脱pH值的预测效果尤其好,所有预测的平均误差分别为0.2和1.6个pH单位,而其他一些特性的预测效果则明显较差。本文介绍了竞赛的过程、方法和结果,可作为教程以及供其他人进行内部基准测试的参考。各组织在方法披露政策上存在差异,但大多数管理层对“高地运动会”活动非常配合,从所提供的方法中可以深入了解常见和最佳实践。积累的数据集将作为计算机预测工具进一步开发的基准测试工具。

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