When Marc Andreessen and Ben Horowitz founded their namesake venture firm in 2009, they laid out a clear-but-narrow vision for investing in a new wave of Web-based innovation.
Andreessen, in particular, espoused a net-centric view that was absolute. “No clean tech, no rocket ships, no electric cars. No China or India,” he told Fortune magazine at the time. Biotech likewise was out of the question. In the six years since then, Andreessen Horowitz has grown into a $4 billion VC, and established itself as a leading tech investor. Andreessen’s observation that “software is eating the world” has become an industry axiom, as Web-based services have invaded and taken over financial services, education, and a host of other sectors.
Now the venture firm also known as A16Z has formed a new $200 million fund to make software investments at the intersection of tech and life sciences, where software companies are developing new ways analyze and process data for biotech and healthcare companies. Money for the firm’s new bio-fund was all new, raised from existing limited partners and not by carving out funding from A16Z’s flagship venture or opportunities funds.
One of the firm’s first investments is TwoXar, a Palo Alto, CA-based tech startup using proprietary algorithms to analyze biological data in both public and proprietary databases with the goal of identifying previously unknown effects of drug candidates in early stage discovery. The idea is to point the way to compounds that could be developed as new drugs for metabolic and neurological disorders.
TwoXar “fits our investment thesis in that they use machine learning and cloud biology,” said Vijay Pande, who joined Andreessen Horowitz as a general partner dedicated to the bio fund.
Pande has defined “cloud biology” as much like cloud computing. In addition to providing computational services, though, Pande has said that Web-based programs also can be used to carry out automated experiments more precisely and consistently than lab technicians (enabling biotech companies to optimize the reproducibility of their scientific results). At Stanford, where Pande was previously a scientist, his lab specialized in