Pharmacokinetic models to design & optimize clinical trials in ovarian cancer

药代动力学模型设计

• 批准号: 6323316
• 负责人: MICHAEL A BOOKMAN
• 金额: $ 4.78万
• 依托单位: FOX CHASE CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-30 至 2000-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6323316
• 关键词: clinical research; clinical trials; combination chemotherapy; disease /disorder model; health science research support; human subject; laboratory rat; ovary neoplasms; pharmacokinetics

DESCRIPTION: (Applicant's Description) Chemotherapy of women with advanced-stage ovarian cancer achieves good initial results with only a limited impact on long-term disease outcomes, as over 80 percent of these patients eventually develop recurrent disease accompanied by a progressive increase in drug resistant tumors. Long-term outcomes might be improved through the development of new chemotherapy regimens, especially through incorporation of agents that exhibit pharmacological synergy. Toxicity of these new regimens has been substantial, and management of hematologic toxicity has thus assumed the dominant role in clinical trial design, without direct or indirect evidence that the desired biologic targets are actually being modulated within the tumor. The number of potential combinations and sequences in daunting, and many promises regimens will be overlooked using a conventional empiric approach to clinical trial design. The overall goals of this application will be to apply and integrate pharmacokinetic (PK) and pharmacodynamic (PD) principles in both preclinical models and clinical trials to select and optimize combination chemotherapy in ovarian cancer patients. We propose to utilize a syngeneic rat model of advanced epithelial ovarian cancer as a translational tool to address biologic questions related to new combination chemotherapy regimens. Hybrid physiologically-based (PB)-PK/PD models can rationally select promising combination protocols that will undergo phase I clinical evaluation in newly diagnosed patients using local and national resources in collaboration with the Gynecologic Oncology Group. PK/PD measurement inpatients will be integrated in a population-based PK-PD modeling strategy to identify and account for patient variables. This will further refine the treatment regimen and facilitate the design of individualized drug regimens. Overall, it is proposed that through the quantitative nature of PK/PD models, identification of rational combination regimens with significant impact on ovarian cancer will be expedited.

描述：（申请人的描述）晚期卵巢癌女性的化疗取得了良好的初步效果，但对长期疾病结果的影响有限，因为这些患者中超过 80% 最终会出现复发性疾病，并伴有耐药肿瘤逐渐增加。通过开发新的化疗方案，特别是通过结合具有药理协同作用的药物，可以改善长期结果。 这些新疗法的毒性很大，因此血液学毒性的管理在临床试验设计中占据了主导地位，但没有直接或间接证据表明所需的生物靶标实际上在肿瘤内受到调节。 使用传统的经验方法进行临床试验设计时，潜在的组合和序列的数量令人畏惧，并且许多有希望的方案将被忽视。 该应用的总体目标是在临床前模型和临床试验中应用和整合药代动力学（PK）和药效（PD）原理，以选择和优化卵巢癌患者的联合化疗。我们建议利用晚期上皮性卵巢癌的同基因大鼠模型作为转化工具来解决与新的联合化疗方案相关的生物学问题。 基于混合生理学 (PB)-PK/PD 模型可以合理选择有前途的组合方案，这些方案将与妇科肿瘤学组合作，利用当地和国家资源对新诊断的患者进行 I 期临床评估。住院患者的 PK/PD 测量将整合到基于人群的 PK-PD 建模策略中，以识别和解释患者变量。 这将进一步细化治疗方案，有利于个体化用药方案的设计。 总体而言，建议通过 PK/PD 模型的定量性质，加快确定对卵巢癌具有显着影响的合理联合治疗方案。