Shiri Parisa, Lai Veronica, Zepel Tara, Griffin Daniel, Reifman Jonathan, Clark Sean, Grunert Shad, Yunker Lars P E, Steiner Sebastian, Situ Henry, Yang Fan, Prieto Paloma L, Hein Jason E
Department of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Amgen Inc., Cambridge, MA 02141, USA.
iScience. 2021 Feb 12;24(3):102176. doi: 10.1016/j.isci.2021.102176. eCollection 2021 Mar 19.
Solubility screening is an essential, routine process that is often labor intensive. Robotic platforms have been developed to automate some aspects of the manual labor involved. However, many of the existing systems rely on traditional analytic techniques such as high-performance liquid chromatography, which require pre-calibration for each compound and can be resource consuming. In addition, automation is not typically end-to-end, requiring user intervention to move vials, establish analytical methods for each compound and interpret the raw data. We developed a closed-loop, flexible robotic system with integrated solid and liquid dosing capabilities that relies on computer vision and iterative feedback to successfully measure caffeine solubility in multiple solvents. After initial researcher input (<2 min), the system ran autonomously, screening five different solvent systems (20-80 min each). The resulting solubility values matched those obtained using traditional manual techniques.
溶解度筛选是一个必不可少的常规过程,通常劳动强度很大。已经开发出机器人平台来自动执行一些涉及的体力劳动。然而,许多现有系统依赖于传统分析技术,如高效液相色谱法,该方法需要对每种化合物进行预校准,且可能消耗资源。此外,自动化通常不是端到端的,需要用户干预来移动小瓶、为每种化合物建立分析方法并解释原始数据。我们开发了一种具有集成固体和液体加样能力的闭环、灵活机器人系统,该系统依靠计算机视觉和迭代反馈成功测量了咖啡因在多种溶剂中的溶解度。在研究人员最初输入(<2分钟)后,系统自主运行,筛选了五种不同的溶剂系统(每种20 - 80分钟)。所得溶解度值与使用传统手动技术获得的值相符。