How to Build a Billion-Dollar Company (And Keep An Academic Day Job), According to David Walt

Anyone compiling a list of the most successful life sciences entrepreneurs of the past decade would have to consider a soft-spoken academic named David Walt. He’s the chemistry professor at Medford, MA-based Tufts University who co-founded Illumina in 1998.

San Diego-based Illumina (NASDAQ: ILMN) found its niche in the past decade by boosting the efficiency of fiber-optic sensors to do high-speed analysis of genes, and the subtle ways they can get turned on or off. It’s one of the bigger success stories in San Diego’s biotech cluster, having grown to 1,600 employees and a stock market valuation of more than $4 billion.

I spoke with Walt last week when he was in Seattle to give a keynote presentation at a bioengineering entrepreneurship symposium organized by professor Buddy Ratner at the University of Washington. During his talk, Walt offered some valuable lessons learned from his Illumina experience to young scientists thinking about the entrepreneurial leap.

Walt, 56, urged the young scientists to align themselves with seasoned venture capitalists, who can introduce them to people with the best business skills to implement a new idea. His big break came one day when he gave a talk about his research at The Scripps Research Institute in San Diego, and venture capitalist Larry Bock was in the audience. Bock followed up with him to learn more, and ended up providing seed capital to Illumina, along with Arch Venture Partners and Venrock Associates.

“A lot of this has to do with human relationships, and the serendipity of who you bump into,” Walt said.

While Walt encouraged scientists to think about entrepreneurship, he warned them they have to be willing to accept the realities of business. “Decisions get made at a company for business. The goal is to make money, not to support your lab,” he said.

And, while starting a company that ultimately succeeds can pay off for years’ worth of royalty streams and the coolest new “widgets” to keep an academic lab doing groundbreaking science, there isn’t much glory in it, he said.

“Don’t do it for your ego,” Walt said. “If you’re successful, you will not be recognized. The only people who will know who you are on the board of directors and senior management. You need to prepare for that.”

I followed up with Walt after his talk to ask about some things he didn’t cover, including the race to make gene sequencing better, faster, and cheaper—and his thoughts on his latest idea for a company that he hopes will make it big, Cambridge, MA-based Quanterix.

Here are edited highlights from the exclusive interview:

Xconomy: There’s been a lot of talk lately about bringing down the cost of sequencing entire human genomes to $5,000. Is that really possible or realistic?

David Walt: Absolutely. I think the $5,000 genome is going to be here within a couple years. Right now, Illumina has announced it can do consumer sequencing for $40,000. The expectation is that there will be a decrease in the price in the next few years. That’s for raw sequence. People are still going to have to access bioinformatics to be able to interpret the genome. But for raw sequence, the scientific community is probably not going to be that far off from the $1,000 genome in three or four years.

X: Is there some peril in this race when people are trying to bring the cost down this quickly? Are we going to get a lot of errors, bad sequences from this?

DW: No. There’s a lot happening on the assay side, the molecular biology side, in terms of the enzymes being used for sequencing. They are being engineered to be better. The reagents are being designed to be more pure. So the error rate is decreasing, and the quality of the chemistry and biochemistry is improving at the same time as the throughput of the instruments is increasing.

X: How far ahead do you think the technology is getting beyond the biology? Do people have any idea what to do with all these sequences? What kind of experiments does this open up for biology?

DW: This is kind of the great debate between hypothesis-driven research, where you have specific scientific questions you ask, and correlation science, in which you gather the data first and then see if you can figure out what’s going on. We’re at the stage where there’s enough capability in genotyping and sequencing, and we’re on the cusp of seeing these two approaches come together. A lot of hypotheses out there in biology will be addressed by being able to put these high-throughput techniques to work.

The original hope was that you’d do these genome-wide association studies, and you’d understand the molecular basis of things like Type 2 diabetes, and understand lupus, lung cancer, breast cancer and everything else. It turns out these are multigenic diseases. There are likely to be many different factors in play, spread widely across the genome, that lead to complex interactions and result in disease. A single mutation such as sickle-cell anemia, for example, with a point mutation, is not the common type of genetic disease. Usually it’s a matter of multiple sites, and multiple variants that play a role in disease. Through the sequencing efforts, we’ll discover many of the rare SNPs [single nucleotide polymorphisms]. In the next round of Genome Wide Association Studies (GWAS) we’re going to learn a lot more. The next round of papers isn’t going to say, ‘This particular SNP was responsible for 8 percent increase in risk for Type 2 diabetes.’ It’s going to say, ‘Here’s the map of Type 2 diabetes,’ which we’ll begin to understand by genotyping hundreds of thousands or millions of people. We’re going to begin to understand the real genetic underpinnings of disease.

That doesn’t eliminate the fact that’s there’s another layer of complexity involved, and that’s environmental factors. You have to look at the context of the environment in which your genetic makeup is immersed. People who live in New Orleans are probably going to be more prone to obesity, because they’re eating rich, fatty foods, than, say, people who live in California. They’re immersed in an environment where such factors will have a stronger influence.

X: So when people say we’re going to sequence all the genomes and it’s going to lead to personalized medicine, it sounds like you’re saying, ‘Hold on, this is going to take longer, it’s more complicated.” Is that right?

DW: Over the next couple of years, we’re going to know a lot more than we ever did before. The expectation back in 2000 when the completion of the Human Genome Project was announced, was that biology was solved and we would understand all these diseases. That expectation was a very simplistic view of things.

These discoveries will be a 50 to 100-year kind of thing. We’re going to continue to learn about human disease very broadly. But with all these tools, you asked if we’re getting ahead of the biology. We’re already ahead of the biology. The data being generated are way ahead of the biology. But as long as we don’t lose that data, as we get to 1,000 genomes, 10,000 genomes, 100,000 genomes, or 1 million sequenced, then we’ll be able to use sophisticated tools to mine the data. Eventually we’ll be able to get the answers to some of the key questions.

X: So computing will be the key?

DW: Yes, that’s the limitation. The bioinformatics side is not there yet.

X: So do you have a breakthrough idea for a new company?

DW: We started a new company called Quanterix. It’s based in Cambridge. I can walk to it. It’s focused on single molecule protein detection for early diagnosis. Basically you’re able to measure the levels of proteins at unprecedented levels of sensitivity. One example would be to find very early markers of cancer in blood. You might have a 1 millimeter-cubed tumor that doesn’t pose any threat, but by taking a blood sample you may be able to find proteins it is producing.

X: Maybe you would put people on chemo earlier then?

DW: Maybe, or maybe just monitoring and seeing if the immune system takes care of it and you don’t have to worry about it. But if it continues to grow, you put people on chemo earlier. Then you can see if you’ve done anything effective or not.

X: Could this be the next Illumina?

DW: I hope so.

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3 responses to “How to Build a Billion-Dollar Company (And Keep An Academic Day Job), According to David Walt”

  1. Skeptic Prof says:

    Yikes, it worries me that the realistic pay off for high throughput science is being put on a “decades to hundreds” of years sort of timeline…”translational” approaches are starting to look a lot like “basic science”. I hope we don’t spend all of our money shoveling data into databases with a “someday” payoff…when smaller scale, hypothesis driven research often offers payoffs in short order. In less than a quarter century we have gone from Notch and Wingless in Drosophila to Notch and Wnt in cancer biology…real knowledge with genes whose deeply explored functions are giving real insight…what value exactly is the diabetes map…in a word where Rosetta is sold for parts after Merck says “meh”. Just a little cheerleading for critical outcomes analysis folks…just cause NIH spends money doesn’t mean good science is done.