Cloud Lab

A cloud lab is a real laboratory with real liquids, devices, and measuring instruments. The difference from a normal lab: none of the researchers actually stand inside it. The work is done by robotic arms and automated devices, controlled by computers. Anyone who wants to run an experiment describes it on a screen and sends the job over the internet. A few hours or days later, they get the measurement data back without ever having entered the building. The name alludes to cloud services, that is, computers in other people’s data centers that one uses jointly for a fee.

Why pharmaceutical companies and start-ups rely on it

A well-equipped chemistry or biology lab can easily cost several million euros. For a small start-up, that is out of reach. A cloud lab spreads these costs across many customers, much like a workshop uses its expensive machines for many different orders. This way, a young company can start running experiments for which it would otherwise have to spend years raising money.

The second reason is reliability. In research, a result is only considered solid once others can reproduce it. That is exactly where things often fail because of small differences: one person shakes more vigorously, another waits two minutes longer. Robots do exactly the same thing every time and log every step with a timestamp. Another team can later simply resubmit the same instruction file.

The third reason is the connection with AI. An AI program can suggest which substance should be tested next. Until now, the slow part has always been the actual testing in the lab. If the AI can send its suggestions directly to robots, prediction and testing run in one continuous loop. Such facilities are also called self-driving labs.

From click to test tube

The process begins with a protocol. This is a precise instruction, similar to a cooking recipe, but written in a programming language. It states, for example: take 50 microliters from container A, add it to container B, heat to 37 degrees, wait 20 minutes, then measure the color. The cloud lab checks whether it can carry out these steps with its equipment.

After that, automation takes over. Robotic arms or rail systems transport small plastic plates with dozens of wells between stations. Pipetting robots dispense liquids in amounts smaller than a drop of water. Centrifuges, incubators, and measuring devices are permanently installed alongside. Cameras film everything so customers can check what happened.

The measurement data automatically end up in a database and are immediately available for download. It’s important to distinguish this from simulation: a cloud lab doesn’t calculate anything in advance, it actually experiments. It therefore also has real limitations. Whatever no device in the lab can do cannot be ordered, and the unusual manual tricks of an experienced human are absent.

Providers, university facilities, and headlines

Commercial providers such as Emerald Cloud Lab in California or Strateos have been renting out such capacities for several years already. Large pharmaceutical companies are building their own automated sites to test drug candidates faster. Carnegie Mellon University has a cloud lab that students and researchers use together.

In business news, cloud labs usually turn up in connection with AI-assisted drug development or new battery materials. When a company promises to cut years off research, an automated facility is often behind it. For investors, the interesting question is whether the robots actually lead to usable results faster. Solid figures on this are still rare, and the technology is expensive to maintain.

In everyday life, one encounters this principle in a weaker form. Anyone who gives a blood sample whose analysis runs in a highly automated large laboratory benefits from the same idea. Schools and universities likewise use remote-controlled experimental setups in teaching, so that several classes can use the same expensive device.