The company plans to use the cash for expanding its existing imaging systems and software, as well as pushing forward its ability to help with pre-clinical trials for drug discovery. And 3Scan said it may be able to do that using machine-learning technology.
3Scan builds a device from scratch that can deconstruct any kind of biological soft tissue into microscopically thin, almost transparent slices. At the same time, the machine scans and analyzes those samples like a microscope. The device, called a knife edge scanning microscope, creates three-dimensional imagery from the large datasets it collects.
The result is that 3Scan’s device can take a tissue sample—say, a tumor from a lab animal—and make a 3D map of it. That map might let you see in detail each one of the tumor’s vessels, for instance, or the distance between the branches of those vessels, or even just the surface area of the tumor as a whole. That could open up a host of applications for biotech and pharma drug companies, such as potentially developing more effective, targeted treatments, as Xconomy reported last year.
Now, 3Scan plans to apply machine learning to its automated process, helping potentially deliver more accurate results in drug testing and clinical diagnostics, the company said.
“This type of imaging technology is essential if we want to ever be able to use the power of modern computing to improve pathology outcomes,” chief operating officer and co-founder Megan Kilman said in a prepared statement.
Based on technology developed at Texas A&M, Kilman and Todd Huffman co-founded 3Scan in 2010. The company was funded by Breakout Labs in 2012 and received a $6.7 million Series A round from Lux Capital last year.
In addition to Lux Capital and Data Collective, Dolby Family Ventures, OS Fund, Comet Labs, and Breakout Ventures also joined in the Series B funding. The investment arm of an unnamed U.S. research hospital also participated in the round.