Engineering Personalized Cancer Chemotherapy Schedules

设计个性化癌症化疗方案

• 批准号: 1235182
• 负责人: Robert Parker
• 金额: $ 40万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1235182&HistoricalAwards=false
• 关键词: Engineering; Personalized; Cancer; Chemotherapy; Schedules

1235182/ ParkerThe clinical schedule of administration for anticancer agents is developed currently through a statistically-driven trial-and-error process based on previous experience with similar effective agents, in combination with animal studies and Phase I trials, to establish maximum tolerated dose (MTD) and starting dose for Phase II trials. The result of the ensuing Phase II trial, when successful, is a feasible, but suboptimal, schedule for a drug administered to an "average" patient. But individuals are a population of differences from the "average". The researchers employ a systems medicine approach, interfacing medical practice with rigorous systems engineering tools in an effort to improve the potential outcomes (better antitumor effect; fewer toxic side effects) for patients receiving chemotherapy for treatment of cancer. The mathematical models of disease that they will construct will be derived from mechanism and physiology and informed from available clinical data. With an interest in using these models for the design of novel patient-tailored chemotherapy treatment schedules, the researchers will focus on models that are control-relevant, meaning of suitable complexity to be used explicitly in model-based systems engineering algorithms. Finally, they will explicitly incorporate clinical concerns in the treatment design problem formulation, such that clinical treatment objectives and constraints will provide practical limits on the chemotherapy schedules returned by the design algorithm. With an eye to translating these results efficiently to clinical practice, the researchers focus on two first-line chemotherapeutics: gemcitabine and docetaxel.

目前，抗癌药物的临床给药方案是根据类似有效药物的既往经验，结合动物研究和I期试验，通过药物驱动的试错过程开发的，以确定最大耐受剂量（MTD）和II期试验的起始剂量。 随后的第二阶段试验的结果，如果成功的话，是一个可行的，但次优的，给药的“平均”患者的药物时间表。 但个体是一个与“平均值”不同的群体。 研究人员采用系统医学方法，将医疗实践与严格的系统工程工具相结合，以改善接受化疗治疗癌症的患者的潜在结果（更好的抗肿瘤效果;更少的毒副作用）。 他们将构建的疾病数学模型将来自机制和生理学，并从现有的临床数据中获得信息。 由于有兴趣使用这些模型来设计新的患者定制的化疗治疗方案，研究人员将专注于控制相关的模型，这意味着在基于模型的系统工程算法中明确使用适当的复杂性。 最后，他们将明确纳入临床问题的治疗设计问题的制定，使临床治疗目标和约束条件将提供实际限制的化疗方案返回的设计算法。 为了将这些结果有效地转化为临床实践，研究人员专注于两种一线化疗药物：吉西他滨和多西他赛。