Clinical Practice Data to Aid Narrow Therapeutic Index Drug Classification

项目总结/摘要 具有窄治疗指数（NTI）的药物可导致死亡。对于这些药物， 浓度可能导致严重的毒性或治疗失败。因此，在通用的 在药物开发方面，NTI仿制药达到与参考产品相似的暴露至关重要。到 为了提高NTI药物的治疗等效性，食品和药物管理局已经收紧了他们的 生物等效性标准。然而，这些新标准的广泛实施具有挑战性，因为 一些药物没有确定的NTI分类。这可能是由于缺乏对 药物的治疗范围或剂量/浓度-反应关系。因此，有一个迫切和未满足的 需要一种系统的方法来识别和分类NTI药物。该提案将使用一个独特的 将临床实践数据与统计工具相结合的基础设施，以表征药物剂量/浓度- 反应关系和NTI药物分类。这一建议的核心假设是， 系统方法将导致成功地将具有NTI的药物分类。科恩-沃科维兹博士 通过对公开可用的数据（文献和 数据库）来提取信息并允许用NTI对药物进行分类。因为大量的细节 包括在公开可用的数据库是可变的，科恩-沃尔克维兹博士将补充这一数据与 从杜克大学医学中心的医疗记录中提取的信息。如果有足够的数据 从这两个来源，他将描述候选药物的浓度-反应关系 使用群体药代动力学（PK）-药效学（PD）方法学研究NTI。这个项目 评估一种新的，系统的方法来分类药物与NTI。如果结合公开的数据， 来自医疗记录的补充数据和群体PK-PD方法可以将具有NTI的药物分类， 这将极大地影响公众健康，并简化FDA生物等效性新标准的适用性 与NTI的仿制药。

PROJECT SUMMARY/ABSTRACT Drugs with a narrow therapeutic index (NTI) can cause mortality. For these drugs, small differences in concentrations may lead to serious toxicities or therapeutic failures. Consequently, in the setting of generic drug development, it is critical that NTI generic drugs achieve exposures similar to reference products. To enhance the therapeutic equivalence of drugs with NTI, the Food and Drug Administration has tightened their bioequivalence standards. However, broad implementation of these new standards is challenging because some drugs do not have an established NTI classification. This can be due to a lack in characterization of the drugs' therapeutic range or dose/concentration-response relationship. Therefore, there is an urgent and unmet need for a systematic approach to identify and classify drugs with a NTI. This proposal will use a unique infrastructure to integrate clinical practice data with statistical tools to characterize the drug dose/concentration- response relationship and classify drugs with NTI. The central hypothesis of this proposal is that the proposed systematic approach will result in successful classification of drugs with a NTI. Dr. Cohen-Wolkowiez will evaluate this hypothesis by performing a comprehensive search of publicly available data (literature and databases) to extract information and allow classification of drugs with NTI. Because the amount of detail included in publicly available databases is variable, Dr. Cohen-Wolkowiez will supplement this data with information extracted from medical records at the Duke University Medical Center. If sufficient data is available from these two sources, he will then characterize the concentration-response relationship of candidate drugs with NTI using population pharmacokinetics (PK)-pharmacodynamic (PD) methodologies. This project evaluates a novel, systematic approach to classify drugs with NTI. If the combination of publicly available data, supplemental data from medical records, and population PK-PD methodologies can classify drugs with NTI, this will substantially affect public health and streamline applicability of new FDA standards for bioequivalence of generic drugs with NTI.