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借助用于数据分析和工作流程管理的统一数字平台推动大分子发现。

Advancing large-molecule discovery with a unified digital platform for data analysis and workflow management.

作者信息

Natali Eriberto, Hersch Jana, Freiberg Christoph, Steigele Stephan

机构信息

Genedata AG, Screener Business Unit, Basel, Switzerland.

Genedata AG, Corporate Communications, Lexington, MA, USA.

出版信息

MAbs. 2025 Dec;17(1):2555346. doi: 10.1080/19420862.2025.2555346. Epub 2025 Sep 14.

Abstract

The repertoire of large-molecule treatments continues to expand, resulting in diverse discovery and development workflows. This diversity yields a proliferation of software solutions and procedures for molecule registration, material tracking, experiment planning, data analytics, quality control, data sharing, and decision-making. Contrasting with this manual, labor intensive, and error-prone approach, we introduce the concept of a transformative solution: an integrated platform that translates this complexity into a harmonized, open architecture encompassing all workflows and hardware systems, covering the discovery process up to developability assessment. The benefits and complexities of such a platform are evident in examples spanning different use cases and maturity levels, such as developing multi-specific antibodies and antibody-drug conjugates using shared workflows or incorporating artificial intelligence for predictive and generative tasks. This review outlines state-of-the-art concepts behind a digital platform for automating and streamlining the discovery of new large-molecule treatments.

摘要

大分子治疗方法的种类不断增加,导致发现和开发流程多种多样。这种多样性使得用于分子注册、材料追踪、实验规划、数据分析、质量控制、数据共享和决策的软件解决方案和程序大量涌现。与这种人工、劳动密集且容易出错的方法形成对比的是,我们引入了一种变革性解决方案的概念:一个集成平台,它将这种复杂性转化为一个统一的开放式架构,涵盖所有工作流程和硬件系统,涵盖从发现过程到可开发性评估的整个过程。这种平台的优势和复杂性在跨越不同用例和成熟度水平的示例中显而易见,例如使用共享工作流程开发多特异性抗体和抗体药物偶联物,或将人工智能纳入预测和生成任务。本综述概述了用于自动化和简化新大分子治疗方法发现的数字平台背后的最新概念。

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