Radix Labs


Dhasharath Shrivathsa


Olin College, MIT Media Lab


Robotics, Deep Software & AI, Internet of Things, Biotech & Life Sciences

Automating biology lab processes from experiments to mass production.

For all the wonders of its science, today’s biology lab is inefficient and prone to human error. Its machines, the equipment tasked with unlocking some of life’s most profound mysteries, don’t talk to each other. Humans perform repetitive tasks by hand without precise documentation. Reproducibility of results by peers is difficult or impossible. It is a flawed system.

Radix has built a programming language that unites biologists and their lab machinery in one automated unit. This programming language is the heart of software that manages both human and machine tasks. It is the first time disparate lab machinery can communicate with one another under the control of one centralized platform—it is, for all intents and purposes, an operating system for biology labs.

Shrivathsa, a computer scientist, developed the first iteration of Radix’s core software for Field Programmable Microfluidic Arrays. But he soon understood that his compiler architecture could be applied more broadly. It was different from all existing lab automation scheduling software and represented a potential paradigm shift in the way the biology lab was run. Perhaps most importantly, it reimagined the foundational concept of a lab itself, not as a series of disconnected steps and parts, but as a very big and very real computer.

Shrivathsa quickly realized that for Radix to truly change the way biology is done, its software must be as accessible and fluid as possible—it had to work within the existing infrastructure of the lab and empower, not intimidate, its users.  

Requiring no coding and designed around an approachable user interface, Radix’s software solution intentionally distances the specification of the program—in this case the lab protocol—from the execution. It does this with the hope that biologists spend less time in the lab, and more time focusing on experimental design and analysis. True innovation is born from such a decoupling, as Shrivathsa notes with a smile, “We would never have smartphones if you had to do all the math to engineer one by hand.”

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