Elemental Machines has started shipping its sensor-enabled smart lab system. The system collects data on temperature, oxygen and other variables that can affect the outcome of early-stage research to cut the time it takes scientists to pinpoint the causes of variability and reproducibility problems.
News of the system first emerged in February when Elemental Machines raised $2.5 million from some notable financiers, including Rock Health and the seed-stage offshoot of Peter Thiel’s Founders Fund. By that stage, Elemental Machines had quietly accrued approximately 30 early users of the system, a figure it is looking to increase now through the full commercial introduction of its suite of sensors and data analysis tools.
“We're initially focused on complex processes involving biology and chemistry,” CEO Sridhar Iyengar told FierceBiotechIT. “If you measure temperature, light and humidity, you've got most of the factors that affect the quality of a chemical reaction covered. If you add to that an oxygen and CO2 sensor, now you've got most of biology covered. With literally half a dozen sensors you've got most of the confounding variables that will affect the quality of chemistry and biology pretty much covered.”
Those sensors, while critical to Elemental Machines’ offering, are more of an enabler of the system than the star of the show. For Iyengar, the real value lies in what Elemental Machines does with the data it collects, particularly when it looks at variation over time.
One client, for example, had two independent heating, ventilation and air conditioning (HVAC) units at its building, but didn’t know which rooms were covered by which system. By analyzing patterns in the sensor data, Elemental Machines categorized the rooms and offered an explanation for why experiments wouldn't work when transferred from one lab to another.
Elemental Machines is the third company founded by Iyengar--the second, Misfit Wearables, sold to Fossil Group for $260 million last year--and represents the manifestation of an idea that has bubbled under since before he became an entrepreneur 15 years ago. As an electrical engineering undergrad starting a PhD in biological sciences, Iyengar was surprised by the level of variability tolerated in life sciences. Then, when his first startup had a problem with yields, Iyengar put sensors on the assembly line, analyzed the data and took steps to improve output.
The penny really dropped at Misfit.
“We were able to gather sensor data ... from millions of people around the world, shoot that data to the cloud in real time, do real-time processing and give real-time insights back to these millions of people all within a matter of a few seconds and for fractions of a penny,” Iyengar said.
The technology stack that enabled Misfit to collect and process the data is well established, but is yet to take hold in life science research to the same extent as in the consumer space. Companies such as preclinical CRO Vium are changing that, but Iyengar thinks there is an opportunity to make it easier for drug developers to adopt sensor-enabled systems at their own labs by providing the tech knowhow they lack.
“People who know how to take DNA out of a firefly and stick it into a mouse and make it glow in the dark aren't necessarily the ones who know how to build hardware, manage Bluetooth connections to a smartphone, manage Amazon Web Services and write all those tools,” Iyengar said.