'We like to think of ourselves as the lead turtle in the race of the turtles': How Big Pharma is turning to Silicon Valley to supercharge drug development

jay bradner

Pharmaceutical companies are finding ways to take cues and apply new tools from Silicon Valley with the goal of speeding up drug development.
It's leading to new kinds of scientists who are fluent in both biology and computer code and virtual trials that could make drug development more efficient.
But it's happening in an industry that has been slow to adopt these kinds of technologies. "Our field has been a late adopter to innovations that the computer-science world is sick of talking about," Novartis' president, Jay Bradner, said.

Pharmaceutical companies are slowly but surely turning their eyes toward Silicon Valley.

At a time when companies like Amazon and Apple are getting serious about entering the healthcare market, pharmaceutical firms in turn are considering ways they can learn from their tech counterparts.

But it has taken a long time to get there, Jay Bradner, the president of the Novartis Institutes for BioMedical Research, told Business Insider in an interview at a healthcare conference in Boston this past week.

"Healthcare is so technology forward, and biomedical discovery is so technology forward," he said. "Yet our field has been a late adopter to innovations that the computer-science world is sick of talking about." For example, he said, concepts like machine learning and artificial intelligence are standard for the tech world but new to biomedicine.

Novartis is taking a lot of that computing technology inherent to Silicon Valley and applying it to drug discovery.

"We like to think of ourselves as the lead turtle in the race of the turtles," Bradner said. About 4% of the 6,000 scientists working at Novartis' research engine are data scientists, and the company's biologists also have an understanding of computer science and coding.

"To interact with data today, the fundamental biologist needs to be comfortable 'in silico,'" i.e., through computers, he said. "It's too late for me to go back and learn Python, but every new graduate student from my lab will leave learning how to interact primarily with their data."

Ideally, the thinking goes, pharmaceutical researchers can use these skills and tools like machine learning to speed up drug development.

Virtual trials

One way Novartis put technology to use recently was in determining which trial the company wanted to pursue on an experimental drug.

Novartis was able to take data it had recorded from other clinical trials it had run and use that information to set up virtual trials. These trials looked at how experimental drugs might work. In the end, one of the trials seemed to show that its drug worked, while the other two didn't.

Running the trial virtually allowed Novartis to prioritize how to spend its time and resources.

"In the one case, we're more efficient because we didn't launch and resource two clinical trials, and in the other we can revisit that idea with a definitive trial," Bradner said.

Leaving Silicon Valley culture to the Valley

When it comes to Silicon Valley's culture, with its traditionally hyped-up ideas and "move fast and break things" pace, that's less likely to rub off on pharma.

"Silicon Valley seems to tolerate more hype than the biomedical research environments where I've worked," Bradner said. Still, it doesn't mean researchers within pharma don't have big visions. "It doesn't make this community that we're in any less ambitious or starry-eyed or dreamy," he said.

And while an idea for a new app in Silicon Valley can get off the ground and onto the market in months, the timeline to get a drug from discovery to approval can take upward of a decade and involves a lot of regulation.

As interest from technology companies to get into healthcare and biotech grows, pharmaceutical companies and tech giants are starting to become rivals. But Bradner said the two industries would ultimately be better off teaming up than finding themselves in competition.

"These are two communities that I find really fascinating," he said, "that stand to benefit more from working together than by pretending to have solved each other's problems."

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