Pharma, Startups

Proteus alum’s stealth startup Mousera raises $20M

Mousera, the brainchild of Proteus alum Timothy Robertson, is building a data-heavy platform to accelerate preclinical drug discovery and development.

The stealth startup led by Proteus alum Timothy Robertson just raised $20 million – with aims to “bridge the cultural gap” between Silicon Valley and the life sciences.

Bay Area startup Mousera is building a platform to accelerate preclinical drug discovery and development – and it’s still keeping its technology quite close to the chest. However:

“There are many places in drug development where data collection is still done the same way it was in the 1950s – in quantity and how it’s analyzed,” Robertson said in a phone interview.

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“We saw real opportunities using modern sensor technologies – the things driving the internet of things, or the components in your cell phone,” Robertson continued. “These things can just collect vastly more information about preclinical drug development, and help companies make better judgments.”

Mousera’s $20 million Series B round was led by Data Collective, Robertson said. Other investors include Lux Capital, the Dolby Family, Ame Cloud Ventures and Founders Fund. Last year, the company closed out an $8.8 million Series A, and a $1.2 million seed round.

This isn’t an in silico play, Robertson said.

“We’re more on the other end of the spectrum,” he said. “Our technology is actually very physical.”

It’s in the midst of an invitation-only beta program, testing a select contingent of drug companies’ products to find out if they’re safe and effective.

The company’s growing its personnel, thanks to the new funding – hiring preclinical scientists and engineers specializing in advanced computer techniques like machine learning and large scale data structures.

“Much of what we’re doing is bridging the cultural gap between hard silicon valley technology – electronics, sensors, big data processing, and the life sciences,” Robertson said. “We have a lot of really smart people in the life sciences, but they don’t have the technological background to develop the data platforms and statistics we’re creating.”