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.

项目摘要/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年估计每年60,000例。PDAC经常在高级阶段被诊断出来，从而排除 大多数患者的手术切除。虽然新的系统治疗方案的生存率提高了，但可用性 有多种选项，没有工具来从这些选项中选择最佳方案（以个性化的基础）创建 临床决策中令人沮丧的悖论。由于缺乏个性化的预测工具，当前标准 护理治疗策略的基于预后因素，例如年龄，阶段，性能状态，血清白蛋白， 等等。有一个至关重要的，紧急和未满足的需要开发可以识别最佳系统性的预测工具 治疗方案并从个性化的基础上消除了无效的选择，以改善 生活质量并减少过度治疗。 Cerflux，Inc。正在以低成本开发这种预测技术 和快速个性化的肿瘤学测试（诗人）使每个患者与正确的治疗相匹配 - 之前 治疗 - 在短期内改变胰腺癌治疗，并改变 世界各地的患者和提供者。我们的个性化医学方法是独一无二的，进一步增强了 由Cerflux，Inc。和O'Neil综合癌症中心之间的商业学术合作 在伯明翰阿拉巴马大学。拟议的项目将基于我们团队最近的工作，包括 专利（美国10,114,010B1）的仿生型在体外平台用于药物运输和胰腺 微动物肿瘤模型。该提案的商业目标是确定使用诗人的最佳实践 个性化疗法。我们的假设是，在诗人中观察到的对治疗的反应将近似 相应患者的反应。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，每个患者。我们提出以下目的以实现我们的目标： 目标1：使用人PDAC细胞系Xenographographics校准和优化用于评估治疗的诗人 随后对患者组织进行测试。 目标2：在个性化的基础上评估各种系统治疗剂的效率 在个性化治疗中使用诗人的方案和最佳实践。 我们设想Cerflux，Inc。和O'Neil之间的实质性持续的商业学术合作 伯明翰阿拉巴马大学的综合癌症中心，包括机器的整合 学会得出“诗人分数”（一个个性化的定量效率得分） 因素。诗人和诗人分数的数据将有助于临床团队对个别患者的治疗排名 在第一次输注之前。如果成功，这项以SBIR驱动的研究有可能改变胰腺 近期癌症治疗，并对世界产生积极影响。