Software venture giant Andreessen Horowitz just made a major pivot in its strategy: It’s folding biotechnology into its software-heavy portfolio, with a new $200 million fund to fuel startups that integrate biology and software.
This is notable because the venture capital firm, when launched in 2009, was fairly adamant about keeping its investments within its area of expertise: Software. But the healthcare field’s draw is clearly too compelling to pass up. The firm’s core areas of interest are computational biomedicine and digital, beyond-the-pill approaches to therapy.
“The firm has been excited about this space for a while, and we’ve made investments before even raising a bio fund,” writes Vijay Pande, a general partner at Andreessen Horowitz that will lead the fund, in a blog. “But we want to do something really big, and expect this to grow bigger in time, so establishing a separate fund is also about our thinking years down the road.”
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After all, this intersection of tech and biotech is a proving to be a sweet spot for many companies. Next-generation sequencing, for instance, is generating a huge amount of data that needs to be analyzed – and biotech companies are looking to Silicon Valley for help. Google’s life sciences division, Apple’s ResearchKit and IBM Watson are three notable examples of melding biotech and tech.
Pande cites the marketing budget that Google goes after – saying that it’s chasing $200 billion in potential ad revenue. In comparison, the U.S. healthcare budget is $2 trillion – providing a far more vast opportunity to carve out a niche for life sciences-driven software.
“The bio fund is really about funding software companies in the bio space,” Pande writes. “Whereas traditional biotech has very little software in it, at its core.”
The fund’s already invested in a $3.4 million seed round in bioinformatics startup twoXAR, which conducts predictive analytics on which diseases and drug candidates can match up.
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Pande applies the concept of Moore’s Law to biotechnology – with particular interest in the lowering costs of sensor technology and next-generation sequencing. He’s also interested in the application of machine learning in healthcare, because “a big part of medicine involves images,” he writes – in the form of x-rays, or dermatological and ophthalmic imaging.
“When I’m talking to entrepreneurs I like going deep with them not just on protein biology but on machine learning, distributed systems, infrastructure — or even just general issues with healthcare and medicine,” Pande writes.
