What do labs do when faced with large amounts of imaging data? Powerful cloud computing systems have long been the answer to that question, but a new riposte comes from SPACe.

That’s the name of a new open-source image analysis platform designed by researchers at Baylor College of Medicine, Texas A&M University and the University of Houston.

SPACe, or Swift Phenotypic Analysis of Cells, was created to be used on standard computers that even small labs can access, meaning cellular analysis using images produced through cell painting has a lower barrier to entry than ever before.

“The pharmaceutical industry has been accustomed to simplifying complex data into single metrics. This platform allows us to shift away from that approach and instead capture the full diversity of cellular responses, providing richer, more informative data that can reveal new avenues for drug development,” Michael Mancini, professor of molecular and cellular biology and director of the Gulf Coast Consortium Center for Advanced Microscopy and Image Informatics co-located at Baylor College of Medicine and TAMU Institute for Bioscience and Technology.

SPACe is not only accessible because of its less substantial computational needs. Because the platform is open-source, it’s available to anyone who needs it. And it can be used by academic and pharmaceutical researchers alike.

“The platform allows for the identification of non-toxic effects of drugs, such as alterations in cell shape or effects on specific organelles, which are often overlooked by traditional assays that focus largely on cell viability,” says Fabio Stossi, currently a senior scientist with St. Jude Children’s Research Hospital, the lead author who was at Baylor during the development of SPACe.

The platform is a better means than ever of analyzing thousands of individual cells through automated imaging platforms, thereby better capturing the variability of biological processes. Through that, SPACe allows scientists an enhanced understanding of the interactions between drugs and cells, and does it on standard computers, translating to scientists performing large-scale drug screenings with greater ease.

"This tool could be a game-changer in how we understand cellular biology and discover new drugs. By capturing the full complexity of cellular responses, we are opening new doors for drug discovery that go beyond toxicity,” says Stossi.

And the fact that it’s open-source allows scientists to access SPACe for free right now. Researchers interested in using the platform can access it through Github at github.com/dlabate/SPACe. This early version could already make waves in research, but the team also plans to continually improve their product with the help of collaborations with other institutions.