Data Analytics for High Throughput Drug Screens

这项拨款将通过开发设计和实施癌症患者精准药物治疗的技术，为促进国家繁荣和经济福利做出贡献。单个肿瘤通常包含异质细胞，这些细胞对不同药物治疗的反应不同。即使是很小的耐药细胞亚群也可能导致肿瘤复发和治疗失败。该项目将开发工具，根据肿瘤对治疗的反应来识别肿瘤中存在的不同细胞亚群，从而为癌症患者制定个性化治疗计划，并开发混合信号反卷积的新方法。相关的教育活动将包括指导研究生和本科生，开发与工作相关的课程内容，以及为高中生开设短期暑期学校。这笔拨款将利用亚群对所研究药物的差异反应来确定亚群，并量化其初始比例以及个体剂量反应。假设子种群之间没有相互作用的模型以及同时具有线性和非线性相互作用的模型将被考虑。这需要基于捕获潜在细胞种群动态的非马尔可夫过程模型的样本路径轨迹的似然函数的近似值来制定统计推断问题。参数估计的辨识需要解决具有高度非线性和非凸目标函数的约束优化问题。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This grant will contribute to the advancement of national prosperity and economic welfare by developing techniques for the design and implementation of precision drug treatments for cancer patients. A single tumor typically contains heterogenous cells that differ in their response to different drug treatments. Even small subpopulations of drug-resistant cells may cause tumor recurrence and therapeutic failure. The project will develop tools to identify the distinct sub-populations of cells present in the tumor based on its response to therapy, leading to personalized treatment plans for cancer patients and the development of new methodologies for deconvolution of mixed signals. The associated educational activities will include mentoring graduate and undergraduate students, developing course content related to the work, and short summer school for high-school students.This grant will use the differential response of the sub-populations to the drug under study to identify subpopulations and quantify their initial fraction as well as their individual dose response. Models assuming no interactions between the sub-populations as well as models with both linear and nonlinear interactions will be considered. This requires the formulation of statistical inference problems based upon approximations of the likelihood function of sample path trajectories of non-Markovian process models capturing the underlying cellular population dynamics. Identifying estimates of the parameters requires solving constrained optimization problems with highly nonlinear and non-convex objective functions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.