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Automated Solubility Screening Platform Using Computer Vision

preprint
submitted on 06.11.2020, 04:35 and posted on 09.11.2020, 20:50 by Parisa Shiri, Veronica Lai, Tara Zepel, Daniel Griffin, Jonathan Reifman, Sean Clark, Shad Grunert, Lars Yunker, Sebastian Steiner, Henry Situ, Fan Yang, Paloma Prieto, Jason Hein

Solubility screening is an essential, routine process that is often labour intensive. Robotic platforms have been developed to automate some aspects of the manual labour involved. However, many of the existing systems rely on traditional analytic techniques such as High Performance Liquid Chromatography or HPLC, which require pre-calibration for each compound and can be prohibitively expensive. 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 robotics 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 data matched values obtained using traditional manual techniques.

History

Email Address of Submitting Author

parsh1992@gmail.com

Institution

University of British Columbia

Country

Canada

ORCID For Submitting Author

0000-0002-1994-4445

Declaration of Conflict of Interest

no conflict of interest

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