How The Cloud Can Solve Life Science’s Big Data Problem | 7wData

How The Cloud Can Solve Life Science’s Big Data Problem | 7wData

These days, biotech R&D is as much a data problem as a science problem.

Here’s why: in the past decade, the exploding field of synthetic biology has done an incredible job solving the scientific challenges of making biology easier to engineer. I have written about how tools like gene editing, synthesis, sequencing, and automation are changing for the better the way we feed, fuel, heal, and build our world with biology.

But these new techniques have created a new challenge that the life science industry wasn’t ready for: how to get massive amounts of super complex data into a single place where it's all interlinked and can be fully made into real insights. 

“data science and software engineering problems are now front and center for the life sciences industry,” says Sajith Wickramasekara, CEO and co-founder of Benchling, a San Francisco-based start-up focused on this very problem. “My vision is that once the industry is digitized, you're going to unlock a lot of potential for breakthrough science.”

He’s thinking about new medicines, new kinds of food at the grocery store, new performance clothing from cell-based fabrics — a new generation of chemicals and materials made using high-tech fermentation, the process that gives us beer, bread, and cocoa.

“What I'm really excited about are all the applications we haven't even thought of yet,” he says.

Nowadays, biotech startups are founded with data science in mind. Data science is a greater part of their business and their research infrastructure is oriented around how to capture and learn from the large amounts of data available to them. They aren’t bound to legacy data systems, so in some sense they have an advantage over established companies because, well, it’s easier to start from scratch. 

“If you look at a company like Zymergen, they built their infrastructure from day one to leverage all the great advancements in computer science and machine learning from other industries,” says Wickramasekara. 

Obviously, startups have different constraints. “There are fewer resources and more existential questions over the long run,” Wickramasekara says. In general, though, he believes that they are very well poised to take advantage of the tools and technologies of synthetic biology to innovate and produce at unprecedented speed.

And make no mistake: enterprise companies are learning from their younger rivals. Not only are these large companies embracing the same tools, but many of these small innovators will become parts of bigger organizations down the road. “There's a lot of M&A in life sciences, and so I think you'll see a lot of larger, more established pharma companies using their balance sheets to acquire some of the new biotechs and bring that expertise in-house.”

Wickramasekara jokes that anyone with a laptop and a Red Bull can come to the conference room and prototype their biotech idea. But he’s serious about the power of the cloud to give innovators the ability to tap into powerful on-demand tools and infrastructure. 

“Our goal should be to democratize and decentralize the creation and running of a biotech so that geography and capital to build out a lab doesn’t limit innovation,” he says. 

Gone are the days when you need to raise millions of dollars of venture capital to stand up data centers before you can even get a product to market and begin testing it. Today, small teams of innovators may not even be in the same place, or depend on on-demand specialized expertise from far places. In this environment, researchers depend on a suite of cloud applications to design DNA, collaborate on experiments, manage research workflows, and make critical R&D decisions.

He believes that computational advances in biology — paired with third-party contract research organizations (CROs) and entities like Amazon Web Services and Google Cloud — may enable you or me to conceive of and run a small biotechnology company from our laptop within five years.

Images Powered by Shutterstock