蓝图
计算机科学
生化工程
生物信息学
计算生物学
选择(遗传算法)
纳米技术
化学
人工智能
生物
材料科学
工程类
生物化学
机械工程
基因
作者
Carl Mieczkowski,Xuejin Zhang,Dana Lee,Khanh Nguyen,Wei Lv,Yanling Wang,Yue Zhang,Jackie Way,Jean‐Michel Gries
出处
期刊:mAbs
[Landes Bioscience]
日期:2023-03-07
卷期号:15 (1): 2185924-2185924
被引量:58
标识
DOI:10.1080/19420862.2023.2185924
摘要
approaches, molecular engineering, production, analytical and biophysical characterization, stability and forced degradation studies, and process and formulation assessments. More recently, it is apparent these activities not only affect lead selection and manufacturability, but ultimately correlate with clinical progression and success. Emerging developability workflows and strategies are explored as part of a blueprint for developability success that includes an overview of the four major molecular properties that affect all developability outcomes: 1) conformational, 2) chemical, 3) colloidal, and 4) other interactions. We also examine risk assessment and mitigation strategies that increase the likelihood of success for moving the right candidate into the clinic.
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