Log into a website, click on a project, set a few options, such as the kind of cells to use and the number of replicates, and then click a launch button and wait. The website links to a cloud-based lab that confirms the setting for the experiments. If everything looks good, software places the experiment into a robotic queue. When the experiment reaches the front of the line, robots start running the steps. When the experiment is done, the resulting data can be downloaded, from anywhere in the world.
Sound like science fiction? It’s not. It’s Strateos, which describes itself as a company that turns biology into information technology through data and high-throughput robotics. As explained by head of product Benjamin Miles, PhD, the concept “is based on the principle of looking at how cloud computing accelerated the development of technology in the industrial sector and making that concept accessible in life sciences.”
Connecting to a Strateos lab in Menlo Park or San Diego, a user can use the infrastructure as described above. “A user can have assays that they’ve built internally, and we convert them to code and deploy the assays on our infrastructures,” Miles says.
A user picks from a range of processes, including cell-based assays. “There’s a huge opportunity to track changes in a bioprocess and track all of the resulting data,” Miles says. “For any experiment, the Strateos code is auditable, and the code can be deployed to manufacturing.”
The sci-fi feeling of this is just getting started. In the future, Miles envisions biological autonomous agents—software working under its own command—coming up with experiments, running them, and then using the data to come up with the next set of experiments. “This could be used to optimize bioprocessing workflow,” Miles says.
What started off sounding more like sci-fi than reality could take bioprocessing 4.0 to anyone—anyone who wants to prepare experiments and pay for the results from robotic labs at Strateos. Instead of just software as a service, we can now get science that way, too.