Development of an Integrated Mathematical Model for Comparative Characterization of Complex Molecule

复杂分子比较表征综合数学模型的开发

• 批准号: 8882897
• 负责人: Marcus Laird Forrest
• 金额: $ 60万
• 依托单位: UNIVERSITY OF KANSAS LAWRENCE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-10 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8882897
• 关键词: Development; Integrated; Mathematical; Model; Comparative

Summary The overall goal of this proposal is to develop integrated mathematical algorithms to assess the similarity of analytical characterization data comparing multiple batches of two different complex molecules. First, multiple batches of a biopolymer-drug conjugate (hyaluronic acid-cisplatin) and a pharmaceutically relevant glycoprotein (IgG1-Fc) will be prepared. For the IgG1-Fc molecules, we utilize technology to produce six different, well- defined glycoforms, which can be characterized individually and then mixed together in different ratios resulting in varying levels of binding activity to various Fc receptors for subsequent analytical comparability testing. Second, the biological, chemical and physical properties of both complex molecules will be monitored using a wide range of analytical technologies, including during accelerated stability testing to elucidate correlations between physicochemical changes and biological activity. Third, we will then employ a combination of currently available data visualization tools used our laboratories, along with novel mathematical algorithms to be developed in this proposal, to integrate the structural and biological data to provide an overall assessment of their critical quality attributes (CQAs). Finally, the ability of the mathematical algorithm(s) to assess the overall similarity of multiple lots of each complex biopharmaceutical will be validated using appropriate positive and negative controls, and therefore, provide an overall assessment of analytical comparability.

概括 该提案的总体目标是开发集成数学算法来评估 比较多批次两种不同复杂分子的分析表征数据。一、多 批次生物聚合物-药物缀合物（透明质酸-顺铂）和药学相关糖蛋白 将制备(IgG1-Fc)。对于 IgG1-Fc 分子，我们利用技术生产六种不同的、良好的 定义的糖型，可以单独表征，然后以不同的比例混合在一起，从而产生 与各种 Fc 受体的不同水平的结合活性，用于后续分析可比性测试。 其次，这两种复杂分子的生物、化学和物理特性将使用 广泛的分析技术，包括在加速稳定性测试期间阐明相关性 物理化学变化和生物活性之间的关系。第三，我们将结合目前的 我们的实验室使用了可用的数据可视化工具以及新颖的数学算法 该提案中提出，整合结构和生物数据，以提供总体评估 他们的关键质量属性（CQA）。最后，数学算法评估整体的能力 每种复杂生物药品的多个批次的相似性将使用适当的阳性和 阴性对照，因此提供了分析可比性的总体评估。