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Predicting Antibody Developability Profiles Through Early Stage Discovery Screening.
mAbs ( IF 5.6 ) Pub Date : 2020-04-05 , DOI: 10.1080/19420862.2020.1743053
Marc Bailly 1 , Carl Mieczkowski 1 , Veronica Juan 1 , Essam Metwally 2 , Daniela Tomazela 1 , Jeanne Baker 1 , Makiko Uchida 1 , Ester Kofman 1 , Fahimeh Raoufi 1 , Soha Motlagh 1 , Yao Yu 1 , Jihea Park 1 , Smita Raghava 3 , John Welsh 4 , Michael Rauscher 4 , Gopalan Raghunathan 1 , Mark Hsieh 1 , Yi-Ling Chen 1 , Hang Thu Nguyen 1 , Nhung Nguyen 1 , Dan Cipriano 1 , Laurence Fayadat-Dilman 1
Affiliation  

Monoclonal antibodies play an increasingly important role for the development of new drugs across multiple therapy areas. The term 'developability' encompasses the feasibility of molecules to successfully progress from discovery to development via evaluation of their physicochemical properties. These properties include the tendency for self-interaction and aggregation, thermal stability, colloidal stability, and optimization of their properties through sequence engineering. Selection of the best antibody molecule based on biological function, efficacy, safety, and developability allows for a streamlined and successful CMC phase. An efficient and practical high-throughput developability workflow (100 s-1,000 s of molecules) implemented during early antibody generation and screening is crucial to select the best lead candidates. This involves careful assessment of critical developability parameters, combined with binding affinity and biological properties evaluation using small amounts of purified material (<1 mg), as well as an efficient data management and database system. Herein, a panel of 152 various human or humanized monoclonal antibodies was analyzed in biophysical property assays. Correlations between assays for different sets of properties were established. We demonstrated in two case studies that physicochemical properties and key assay endpoints correlate with key downstream process parameters. The workflow allows the elimination of antibodies with suboptimal properties and a rank ordering of molecules for further evaluation early in the candidate selection process. This enables any further engineering for problematic sequence attributes without affecting program timelines.

中文翻译:

通过早期发现筛选预测抗体可开发性概况。

单克隆抗体对于跨多个治疗领域的新药开发起着越来越重要的作用。术语“可开发性”包括分子通过评估其理化性质成功地从发现发展到发展的可行性。这些性质包括自相互作用和聚集的趋势,热稳定性,胶体稳定性以及通过序列工程优化其性质的趋势。根据生物学功能,功效,安全性和可开发性选择最佳抗体分子可简化并成功实现CMC阶段。在早期抗体生成和筛选过程中实施的高效实用的高通量可开发性工作流程(100 s-1,000 s分子)对于选择最佳潜在候选者至关重要。这包括仔细评估关键的可开发性参数,结合亲和力和使用少量纯化物质(<1 mg)的生物学特性评估以及有效的数据管理和数据库系统。本文中,在生物物理性质测定中分析了一组152种各种人类或人源化单克隆抗体。建立了针对不同属性集的测定之间的相关性。我们在两个案例研究中证明,理化特性和关键测定终点与关键下游工艺参数相关。该工作流程可消除具有次优特性的抗体,并消除分子的排名,以便在候选选择过程的早期进行进一步评估。
更新日期:2020-04-20
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