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

摘要 这项提议的总体目标是开发综合的数学算法来评估 分析表征数据比较多批次的两个不同的复杂分子。第一，多个 几批生物聚合物-药物结合物(透明质酸-顺铂)和与药物相关的糖蛋白 将制备(IgG1-Fc)。对于IgG1-Fc分子，我们利用技术生产了六种不同的、好的- 明确的糖形式，可以单独表征，然后以不同的比例混合在一起，从而产生 与不同Fc受体结合活性的不同水平，用于随后的分析可比性测试。 其次，这两个复杂分子的生物、化学和物理性质将通过 广泛的分析技术，包括在加速稳定性测试期间，以阐明相关性 物理化学变化和生物活性之间的关系。第三，然后我们将采用目前的组合 可用的数据可视化工具使用了我们的实验室，以及将被 在这项建议中制定的，以整合结构和生物数据，以提供对 其关键质量属性(CQA)。最后，对数学算法的能力(S)进行总体评估 每种复合生物制药的多个批次的相似性将使用适当的阳性和 负面对照，因此，提供了分析可比性的总体评估。

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.