Development of personalized ex vivo predictive technology for rapidly matching patient tumors with chemotherapy regimens before treatment.

开发个性化离体预测技术，用于在治疗前将患者肿瘤与化疗方案快速匹配。

• 批准号: 10080473
• 负责人: Karim I Budhwani
• 金额: $ 24.91万
• 依托单位: CERFLUX, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-10 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10080473
• 关键词: Age; Alabama; Architecture; Area; Biomimetics; Biopsy; Biopsy Specimen; Cell Death; Cell Line; Cessation of life; Chemotherapy-Oncologic Procedure; Clinical; Collaborations; Comprehensive Cancer Center; Core Biopsy; Data; Development; Devices; Diagnosis; Diagnostic; Diffuse; Drug Delivery Systems; Excision; Exposure to; Future; Goals; Harvest; Human; In Vitro; Infusion procedures; Legal patent; Machine Learning; Malignant Neoplasms; Malignant neoplasm of pancreas; Modeling; Operative Surgical Procedures; Pain; Pancreas; Pancreatic Ductal Adenocarcinoma; Patient Rights; Patients; Performance Status; Pharmaceutical Preparations; Pharmacology; Phase; Preparation; Prognostic Factor; Protocols documentation; Provider; Quality of life; Regimen; Right to Treatments; Serum Albumin; Small Business Innovation Research Grant; Specimen; Surface Properties; Survival Rate; Systemic Therapy; Technology; Testing; Therapeutic Uses; Time; Tissues; Tumor Tissue; Universities; Validation; Work; Xenograft procedure; base; cancer therapy; chemotherapy; clinical decision-making; clinically translatable; commercialization; cost; design; drug testing; effective therapy; efficacy testing; human tissue; image processing; improved; individual patient; ineffective therapies; overtreatment; personalized medicine; personalized predictions; pre-clinical; precision oncology; predictive test; predictive tools; response; screening; standard of care; tissue culture; tool; treatment response; treatment strategy; tumor; tumor xenograft

Project Summary/Abstract Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers with <9% five-year survival rate and an estimated 60,000 deaths/year by 2030. PDAC is often diagnosed at an advanced stage thereby precluding surgical resection for most patients. While new systemic therapy regimens have improved survival, availability of multiple options, without tools to select an optimal regimen from these (on an individualized basis), has created a frustrating paradox in clinical decision-making. Due to a lack of personalized predictive tools, current standard of care treatment strategy is based on prognostic factors such as age, stage, performance status, serum albumin, etc. There is a critical, urgent and unmet need to develop predictive tools that can identify optimal systemic therapy regimens and eliminate from consideration ineffective options, on an individualized basis, to improve quality of life and reduce overtreatment. CerFlux, Inc. is developing such predictive technology with its low-cost and rapid Personalized Oncology Efficacy Test (POET) to match each patient with the right treatment – before treatment – to transform pancreatic cancer treatment in the near-term and make a difference in the lives of patients and providers around the world. Our personalized medicine approach is unique and further enhanced by a commercial-academic collaboration between CerFlux, Inc. and the O’Neil Comprehensive Cancer Center at the University of Alabama at Birmingham. The proposed project will build on recent work by our team including a patented (US 10,114,010B1) biomimetic in vitro platform for pharmacological transport and pancreatic microtissue tumor models. The commercial goal of this proposal is to identify best practices for using POET in personalized therapy. Our hypothesis is that response to treatment observed in POET will approximate the response in the corresponding patient. Our objective is to predict both effective and ineffective treatments for each patient prior to initiating treatment. We propose the following aims to achieve our objective: Aim 1: Calibrate and optimize POET for evaluating therapeutics using human PDAC cell-line xenografts for subsequent testing with patient tissue. Aim 2: Evaluate efficacy of various systemic therapy agents in POET on an individualized basis to establish protocols and best practices for using POET in personalized therapy. We envision substantial continuing commercial-academic collaboration between CerFlux, Inc. and the O’Neil Comprehensive Cancer Center at the University of Alabama at Birmingham including the integration of machine learning to derive a “POET Score” – a personalized quantitative efficacy score – based on a combination of factors. Data from POET and the POET Score will help clinical teams rank treatments for individual patients before the first drug infusion. If successful, this SBIR-driven study has the potential to transform pancreatic cancer treatment in the near-term and make a positive impact around the world.

项目总结/摘要 胰腺导管腺癌（PDAC）是最致命的癌症之一，五年生存率<9%， 估计到2030年每年有6万人死亡。PDAC通常在晚期被诊断，从而排除了 大多数患者手术切除。虽然新的全身治疗方案提高了生存率， 多个选项，没有工具来选择最佳方案，从这些（在个性化的基础上），创造了 临床决策中令人沮丧的悖论。由于缺乏个性化的预测工具，目前的标准 护理治疗策略是基于预后因素，如年龄，阶段，性能状态，血清白蛋白， 等开发预测工具，以确定最佳的系统性，这是一个关键、紧迫和未满足的需求。 治疗方案，并从考虑无效的选择，在个性化的基础上，以改善 提高生活质量，减少过度治疗。CerFlux公司正在开发这种预测技术， 和快速个性化肿瘤疗效测试（POET），以匹配每个患者的正确治疗-之前 治疗-在短期内改变胰腺癌的治疗，并改变人们的生活。 世界各地的患者和供应商。我们的个性化医疗方法是独特的，并进一步加强 由CerFlux，Inc.奥尼尔综合癌症中心（O 'Neil Comprehensive Cancer Center） 在伯明翰的亚拉巴马大学。拟议的项目将建立在我们的团队最近的工作，包括 专利（US 10，114，010 B1）仿生体外平台，用于药理学转运和胰腺 微组织肿瘤模型。本提案的商业目标是确定在以下方面使用POET的最佳实践： 个性化治疗我们的假设是，在POET中观察到的治疗反应将接近 在相应的患者中的反应。我们的目标是预测有效和无效的治疗方法， 在开始治疗之前，每名患者。为实现我们的目标，我们提出以下目标： 目的1：校准和优化POET，以评估使用人PDAC细胞系异种移植物的治疗方法， 随后用患者组织进行测试。 目的2：在个体化的基础上评估各种全身治疗药物在POET中的疗效， 在个性化治疗中使用POET的协议和最佳实践。 我们设想CerFlux，Inc.关于O 'Neil 位于伯明翰的亚拉巴马大学综合癌症中心， 学习获得“POET分数”-个性化的定量功效分数-基于以下组合： 因素来自POET和POET评分的数据将帮助临床团队对个体患者的治疗进行排名 在第一次药物输注之前。如果成功的话，这项SBIR驱动的研究有可能改变胰腺癌。 癌症的治疗，并在世界各地产生积极的影响。