A High Throughput Experimentation Platform for Next Generation Chemical Synthesis

这一博士学位的首要目标是创建一个集成系统，将“从小分子设计到生物检测”的过程所需的时间减少到只有60分钟。该项目的核心将是一个新的自动化高通量合成平台，它直接将准备好检测的小分子的制备与生物学评估联系起来。开发用于自动优化生物活动的简化系统将需要来自许多不同科学领域的投入。这个项目的主要方面将包括：(A)发展一个用于多步骤化学合成的自动化平台，用于“可进行化验”的小分子的化学合成；(B)设计一个将合成平台直接与生物评价连接起来的机器人系统；(C)建立一个反馈程序，将获得的合成数据连接起来；(D)开发能够进行高通量实验的在线工作、分析和纯化方法；(E)建立处理大量合成和生物数据的信息学系统，在此基础上可以建立可预测的合成模型。主要成果包括用于自动化高通量合成的集成平台和用于单个反应优化的预测模型。

The overarching goal of this PhD is to create an integrated system that can reduce the timeframe needed for the 'small molecule design to biological assay' process to just 60 minutes. Central to the project will be a new automated high throughput synthesis platform that directly links the preparation of 'assay ready' small molecules to biological evaluation. The development of a streamlined system for the automated optimization of biological activity will require input from many different areas of science. Key aspects of this project will include (a) the evolution of an automation platform for multi-step chemical synthesis of 'assay ready' small molecules; (b) the design of a robotic system that links the synthesis platform directly to biological evaluation; (c) the creation of a feedback process to connect the acquired synthesis data optimization to enable machine-assisted secondary design; (d) the development of in-line work-up, analytical and purification methods that can accommodate high throughput experimentation; and (e) informatics systems to handle the vast amount of synthesis and biological data, upon which predictable synthesis models can be founded. Key deliverables include an integrated platform for automated high throughput synthesis and a predictive model for individual reaction optimization.