文章基本信息

标题：Automated solubility screening platform using computer vision
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作者：Parisa Shiri ; Veronica Lai ; Tara Zepel 等
期刊名称：iScience
印刷版ISSN：2589-0042
出版年度：2021
卷号：24
期号：3
页码：1-31
DOI：10.1016/j.isci.2021.102176
语种：English
出版社：Elsevier
摘要：SummarySolubility 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.Graphical abstractDisplay OmittedHighlights•We demonstrate a modular, closed-loop robotic platform for solubility screening•Automated solvent titration is informed by computer vision and turbidity monitoring•No human intervention or HPLC analysis is required during the experimental loop•Solubility values obtained by the system match those obtained via traditional methodsOrganic chemistry; organic synthesis; green chemistry; engineering; automation