OPTIMIZED CANCER CHEMOTHERAPY VIA PHARMACODYNAMIC MODELS

说明：（申请人摘要）抗癌药物的测定 剂量通常基于在以下中获得的最大耐受剂量（MTD）： I期试验。由于该药物随后用于II期和III期 III试验，所有患者接受相同的剂量，标准化为身体 体重或体表面积，由MTD决定，因此，防止 使用为个体定制的给药方案。在这种情况下， 许多患者的剂量将不足或过量。本申请 旨在通过使用人口来纠正这些缺陷 药代动力学（PK）和药效学（PD）模型。这样的模型可以 基于以下因素表征药物在个体中的PK和PD特性 群体中的这些属性和个体的协变量，或 患者特定因素（例如，年龄、性别、肾功能）， 可以影响药物的PK和PD。基于人口的模型可以 提供定量平台，以设计个体患者给药 方案以实现期望的PK或PD终点。小说之一 本申请的一个方面是对PD的时间依赖性进行建模 响应，可以随后应用于优化的设计， 药物给药方案。将使用不同的PD建模技术， 描述药物诱导的骨髓抑制（MYLS），一个关键的剂量限制性 许多抗癌药物的毒性。两个大型临床数据库，（1， 现有的约翰霍普金斯肿瘤中心数据库，以及2，正在进行的 Fox Chase癌症中心数据库）将提供一组广泛的PK 和PD（即MYLS）数据，包括患者协变量，以评估PD 拓扑替康（TPT）MYLS的模型，无论是作为单一药物， 组合.每种类型的PD模型都将考虑时间- 测量的TPT血浆浓度与MYLS之间的分离， 以及受试者内和受试者间的变异性。预测 每种PD建模策略的性能将从许多方面进行比较， 从两个大型数据库构建的索引数据集，并进一步 进行严格的bootstrap验证分析。这些程序将 指出最佳建模技术的MYLS，和定量方法 设计个体患者给药方案， 疗法

DESCRIPTION: (Applicant's Abstract) Determination of anticancer drug doses is normally based on the maximum tolerated dose (MTD) obtained in Phase I trials. As the drug is subsequently used in Phase II and Phase III trials, all patients receive the same dose, normalized to body weight or body surface area, dictated by the MTD, thus, preventing the use of a dosing regimen tailored to an individual. In this scenario, many patients will be either underdosed or overdosed. This application is aimed at rectifying these deficiencies through the use of population pharmacokinetic (PK) and pharmacodynamic (PD) models. Such models can characterize a drug's PK and PD properties in an individual based upon these properties in the population and the individual's covariates, or patient specific factors (for example, age, sex, renal function) that can influence the drug's PK and PD. The population-based models can provide a quantitative platform to design individual patient dosing regimens to achieve a desired PK or PD endpoint. One of the novel aspects of this application is to model the time-dependent nature of PD responses that can be subsequently applied to the design of optimized drug dosing regimens. Different PD modeling techniques will be used to characterize drug-induced myelosuppression (MYLS), a key dose-limiting toxicity for many anticancer drugs. Two large clinical databases, (1, an existing Johns Hopkins Oncology Center database, and 2, an ongoing Fox Chase Cancer Center database) will provide an extensive set of PK and PD (i.e. MYLS) data including patient covariates to evaluate PD models for topotecan's (TPT's) MYLS, both as a single agent and in combination. Each type of PD model will account for the time- dissociation between measured TPT's plasma concentrations and MYLS, as well as intrasubject and intersubject variability. The predictive performance of each PD modeling strategy will be compared from numerous index datasets constructed from the two large databases, and further undergo rigorous bootstrap validation analyses. These procedures will indicate optimal modeling techniques for MYLS, and quantitative methods to design individual patient dosing regimens that may improve drug therapy.