Automated solubility screening platform using computer vision

Autor: Parisa Shiri, Veronica Lai, Tara Zepel, Daniel Griffin, Jonathan Reifman, Sean Clark, Shad Grunert, Lars P.E. Yunker, Sebastian Steiner, Henry Situ, Fan Yang, Paloma L. Prieto, Jason E. Hein
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: iScience, Vol 24, Iss 3, Pp 102176- (2021)
Druh dokumentu: article
ISSN: 2589-0042
DOI: 10.1016/j.isci.2021.102176
Popis: Summary: 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 (
Databáze: Directory of Open Access Journals