Statistical Methodology for Characterization of Macromolecular Similarity

项目摘要/摘要 与任何药物一样，批准大分子药物的仿制药需要严格的评估 与参比药物的治疗等效性，以确保类似的疗效和安全性。与.相比 药物是有机小分子，大分子的化学组成和特性 药物--通常是蛋白质或多糖--本身就更加多变，因为这些 分子被产生和分离。有一种方法来确定分子将是有利的 相似性，也就是说，等价性，而不需要在动物和人类身上进行昂贵的体内测试。 该提案的具体目标是开发和测试一种可靠的数据驱动的统计方法 评估不同的治疗大分子样品之间的相似性，无论是来自不同批次还是 改变工艺，或者即使完全由不同的实体生产。这一方法是基于一种基因 设计用于从大型复杂数据集中提取相关特征的算法。 指导这项工作的假设是，通过适当的数据解释和建模，治疗等效性 可以从使用光谱和层析测量确定的分子相似性中推断 这揭示了关键的分子属性，最终负责的重要性质的通用和 参比大分子：疗效、副作用、稳定性等。即使不知道这些是如何 属性指定这些属性，事实上它们指定了这些属性，这意味着该数据是等价的 最好的确定方法不需要活体测试。 引入模型的数据将被收集为多批次的蛋白质和多糖 毒品物质及制品。这些数据将来自各种高分辨率质谱学 方法，高场核磁共振光谱分析，以及其他几种光谱和 用于表征溶液中大分子的层析方法。生物活性数据将是 从已经建立了检测方法的外包测试实验室获得。 拟议研究的结果将成为评价两国间相似性的工作方法。 任何大分子药物的仿制和参考版本。这将使仿制药的审批速度更快 大分子药物的不同版本，从而为这些药物提供更广泛的机会和更低的成本 对治疗许多严重疾病至关重要。

PROJECT SUMMARY/ABSTRACT As with any drug, approval of generic versions of macromolecular drugs requires rigorous evaluation of therapeutic equivalence to the reference drug in order to assure similar efficacy and safety. Compared with drugs that are small organic molecules, the chemical composition and characteristics of macromolecular drugs—typically proteins or polysaccharides—are inherently more variable because of the way these molecules are produced and isolated. It would be advantageous to have a way to determine molecular similarity and, by implication, equivalence without using costly in vivo testing in animals and humans. The specific aim of the proposal is to develop and test a robust data-driven statistical methodology for assessing similarity among distinct samples of therapeutic macromolecules, whether from different batches or altered processes, or even if produced by different entities entirely. The methodology is based on a genetic algorithm designed to extract relevant features from large, complex datasets. The hypothesis guiding the work is that with proper data interpretation and modeling, therapeutic equivalence can be inferred from molecular similarity determined using spectroscopic and chromatographic measurements that reveal the critical molecular attributes ultimately responsible for important properties of the generic and reference macromolecules: efficacy, side-effects, stability, and so on. Even without knowing how these attributes specify these properties, the fact that they do specify them means that this data is where equivalence can best be determined without going to in vivo testing. Data introduced into the model will be collected for multiple lots and batches of protein and polysaccharide drug substances and products. The data will come from an assortment of high-resolution mass-spectrometry methods, high-field nuclear magnetic resonance spectroscopy analyses, and several other spectroscopic and chromatographic methods used to characterize macromolecules in solution. Biological activity data will be obtained from outsource testing labs that have established assays in place. The outcome of the proposed research will be a working methodology for evaluation of similarity between generic and reference versions of any macromolecular drug. This will lead towards faster approval of generic versions of macromolecular drugs, and thereby to broader access and lower cost for these drugs which are critical to treating many serious diseases.