In the heart of Silicon Valley is a biotech laboratory run by robots. They carry out experiments ordered by scientists anywhere in the world who simply login to the lab, describe their project, set options like the cells to use or the types of analyses to perform, and go on to do other things while the robots do the rest.
The Strateos lab in Menlo Park, California is as sophisticated as many research facilities and it becomes more so all the time. In partnership with Eli Lilly, Strateos opened a second robotic cloud laboratory in San Diego this year that focuses on the drug discovery process.
Lilly is using part of this Life Sciences Studio for its own projects. The remaining capacity is available to startups in the biosciences to run their own experiments, providing them access to tools and processes few of them can afford on their own.
Though still rare, fully robotic, remote laboratories like these are the future of drug development and biological research. They’re a clear sign of just how much laboratory automation has advanced. From the early days of handling routine and basic functions like blood chemistries, immunoassay and urinalysis, the cutting edge Life Sciences Studio can synthesize, test, and optimize compounds in pursuit of new drug therapies without human help.
At the Texas Medical Center (TMC) Innovation Institute in Houston, concept automation is tested and demonstrated. One of the most futuristic is YuMi, a product of ABB Robotics, which has a research hub there. Already in use in a handful of facilities, YuMi manages viral antigen testing in one lab and handles tissue, bone, and sterile fluid samples at another.
ABB predicts that by 2025, 60,000 nonsurgical robots, many as versatile as YuMi, will be in use in healthcare. 5,000 deployed in laboratories.
Robots,says Robin Felder, PhD, professor of pathology and associate director of clinical chemistry and toxicology at the University of Virginia School of Medicine, are “beginning to swallow up all of the manual parts of the laboratory.”
But more than that, with the rapid advances in artificial intelligence, Ben Miles, PhD, head of product at Strateos, sees a future where the robots will analyze data to initiate experiments on their own.
We’re not there yet. But as Dr. Dean Ho, Provost’s chair professor of biomedical engineering at the National University of Singapore, said, “At some point, we’ll be able to move beyond solely relying on pre-existing data and algorithm training and prediction making.”
Photo by Daan Stevens on Unsplash