Development of a miniaturized analysis platform for quantitative and time-resolved high throughput-analysis of signaling kinetics in cancer cells

为了模拟和预测复杂的细胞内信号网络的治疗反应，增加计算机模型开发的数据密度是系统生物学和医学的主要目标。本项目的目的是以最少的样品和试剂消耗灵敏和可重复地定量蛋白质。为了实现高通量，样品处理应该是快速和自动化的。在第一个项目阶段，我们开发了一个系统，用于液滴微流控异质性分析。与常规免疫测定相比，将异质免疫测定转移到两相微流体系统将样品消耗减少了至少25倍，同时成倍增加了技术重复的数量。与现有技术（ELISA，免疫印迹）相比，这将样品通量提高了200-1000倍。在项目的第二阶段，我们的目标是进一步提高复杂样品测量的灵敏度。此外，我们还将开发用于患者样本自动测量以及时间分辨酶动力学（微流体体外激酶测定）的系统。

In order to simulate and predict the therapy response of complex, intracellular signaling networks, an increase in data density for the development of computer models is a prime goal in systems biology and medicine. The aim of the present project is to sensitively and reproducibly quantify proteins with minimal sample and reagent consumption. To enable a high throughput, sample processing should be fast and automatable.In the first project phase, we developed a system for heterogeneous assays in droplet microfluid-ics. The transfer of heterogeneous immunoassays to a two-phase microfluidic system reduces sample consumption by a factor of at least 25 as compared to conventional immunoassays, while multiplying the number of technical replicates. This enhances the sample throughput by 200-1000 fold as compared to the state of the art (ELISA, immunoblot). In the second project phase, we aim to further enhance the sensitivity for the measurement of complex samples. Furthermore, we will develop the system for the automated measurement of patient samples as well as for time-resolved enzyme kinetics (microfluidic in vitro kinase assays).