ThinkCyte, a Japan-based cell sorting visualisation spinout from University of Tokyo, has raised $3.2m from seed investors including Osaka University Venture Capital, a VC fund run by Osaka University.
The round also included government-backed research board Japan Science and Technology Agency and seed-stage VC vehicle Real Tech Fund.
ThinkCyte is working on a machine learning system, Ghost Cytometry, that classifies cells at a greater pace and with more precision than alternative methods which cannot accurately discern between specimens with similar sizes and structures, according to the spinout.
Ghost Cytometry analyses raw light waves collected from the cells through a single-pixel detector camera, with the system becoming more accustomed to a cell type’s unique light profile over time.
The process could identify cells within 10 microseconds at a throughput rate of approximately 3,000 cells per second. It has applications in research, clinical settings and direct therapeutic purposes such as flagging up cancer cells present within a patient’s blood circulation.
ThinkCyte expects to join forces with unspecified research institutes later in 2018 to deploy Ghost Cytometry for oncological and regenerative medicine projects. It is due to release a beta-stage prototype of the system for research purposes the following year.
ThinkCyte has raised more than $5m in total, including angel investments and grant funding, according to the latest press release, though the company has not provided further details.
The spinout was co-founded by chief technology officer Sadao Ota, an associate professor at University of Tokyo’s Center for Advanced Science and Technology, together with Issei Sato, a lecturer in machine learning in the Department of Complexity Science and Engineering.
Ota and Sato were assisted by chief executive Waichiro Katsuda.
