A High Throughput Experimentation Platform for Next Generation Chemical Synthesis

该博士学位的总体目标是创建一个集成系统，可以将“小分子设计到生物分析”过程所需的时间缩短到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，直接将“可检测”小分子的制备与生物评价联系起来。为生物活性的自动优化而开发的流线型系统将需要来自许多不同科学领域的投入。该项目的关键方面将包括：(a)用于“可检测”小分子的多步骤化学合成的自动化平台的发展；(b)将合成平台直接连接到生物评价的机器人系统的设计；(c)建立一个反馈过程，将获得的综合数据优化连接起来，使机器辅助二次设计成为可能；(d)发展可容纳高通量实验的在线处理、分析和净化方法；(e)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。主要交付成果包括自动化高通量合成的集成平台和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.