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Biotech Valley

Move over programmers. Silicon Valley is about to meet a new kind of geek.

By Mignon Fogarty

IN 2002, Oracle's Larry Ellison predicted that Silicon Valley will become Cell Valley as biotechnology supplants information technology as the überindustry of the San Francisco Bay Area. So perhaps it's no surprise that nervous engineers and computer programmers often ask me how they can translate their skills to take advantage of the trend.

First, I tell them to chill out. Sure biotech is hot, but it is still a heavily regulated, capital-intensive industry whose products can take decades to reach the market. Even if biotech companies aren't directly developing drugs, tests, devices or reagents regulated by the government, they are still highly reliant on the drug-development industry. Some biotech companies create tools to mine genomic data or products to speed up research, but ultimately they are still selling those products to pharmaceutical companies. The Pharmaceutical Research and Manufacturers of America (PhRMA) reports that it takes 10 to 15 years and an average of more than $800 million to bring one drug to market. How many IT products can you think of that take that much time and cash? So relax, biotech isn't likely to force IT out of the playground.

Second, I tell them that biotech is a fascinating industry where the products you work on have the ability (or at least the promise) to improve human health. So if they're really interested in the field, and not just chasing the next trend, biotech can be an awesome place to be. To generalize, the level of dedication of workers I've seen in biotech far exceeds that of other industries, and I believe it has to do with their belief that their work serves a higher good.

The flip side of the long development time and $800 million price tag attached to new drugs is that pharmaceutical companies are always looking for ways to speed things up and cut costs; and that's where bioinformatics comes in. Drug discovery is becoming increasingly reliant on information. Whether it is DNA sequences of potential drug targets, analysis of protein structures or teasing out the differences in gene expression between people who are sick and people who are well, there is information that needs to be gathered, annotated, organized, analyzed and stored. In addition, companies are looking for ways to automate these processes in order to churn through the vast number of drug leads, DNA sequences and other targets that need to be interrogated.

Right around the time the dotcom bubble burst, the first draft of the human genome was released, creating a flurry of interest in biotechnology. Investors who were looking for the next big thing turned their interest to bioinformatics, which merged their understanding of information technology with biotech.

Thus in 2000 and 2001, bioinformatics companies were forming faster than kids can gobble up Halloween candy, and these companies were paying generous salaries to the rare individuals who could understand both biology and information technology. For a while, it seemed as though bioinformatics had become the next Internet; and perhaps it had, since overinvestment led to a hangover that could rival any child's post-Halloween tummy ache. By 2002, it was reported that there were more than 170 companies in the bioinformatics space, and the funding environment was abysmal. Accordingly, many of these nascent bioinformatics companies, like DoubleTwist of Oakland, shut their doors, and the once-hot job market turned icy.

Today, things seem to have settled out, at least a bit. Richard Hughey, chair of the computer engineering department at the University of California, Santa Cruz—the only university to currently offer bachelor's, master's and Ph.D. programs in bioinformatics—says, "My impression is that [the field] is back to growing again." He observes that graduates are finding jobs a bit quicker than they were in the last couple of years, although he's not wildly enthusiastic, saying the job market is "still right on the borderline." Highlighting the strong growth in academic and certificate programs in bioinformatics, Hughey notes that many of UCSC's Ph.D. students are recruited to faculty positions right out of school. Although completing a Ph.D. can take four to six years—too long to count on obtaining a faculty position right out of school if you're starting now—the growth in faculty positions means that universities expect continuing demand for degrees in bioinformatics.

Hughey's advice to students interested in bioinformatics is "Take lots of math." He believes analytical skills and a strong background in statistics are critical for grappling with the large and complex datasets that are routine in biology. "One of the biggest problems is your dealing with the human genome, which has 3 billion nucleotides in it. If you then take 10 genomes and start comparing them, suddenly you've got 30 billion nucleotides. These are incredibly massive amounts of data, and you'd better have a really good feel for the statistics, so that once you've found something, you can figure out whether it is significant," he explains.

Although Hughey says that he's certainly seen talented biologists make the jump to bioinformatics, in general, he thinks it is easier for people with a strong background in engineering, math, computer science or statistics to learn the biology rather than the other way around. To be successful as a bioinformaticist, these people need enough experience to be comfortable in a wet lab, and while it is not necessary that they can do their own creative biology work in the lab, they have to understand what the issues are, says Hughey.

It's also important to remember that while bioinformatics programs exist and are growing, formal education is not necessarily required to work in the field. "Many people have a background in biology and have taken courses in programming, or a master's in computer science and get started that way. On the other end, there are computer scientists/engineers that learn some biology along the way. It's probably easier for the latter type of folks to get jobs, but I would venture to say that most of the people who are in bioinformatics did not get a Ph.D. in bioinformatics—most come from backgrounds like physics, biophysics, computer science, etc.," says John Shon, director of medical informatics at GenVault, a biological sample archiving company in Carlsbad, Calif.

Whether you have some kind of degree or certificate in bioinformatics, or have just developed the skills on your own to enter the field, Hughey says the career path for a bioinformaticist is similar to that of any engineer; for example, an entry-level person would assist others in the group, eventually move on to developing things and leading groups and eventually becoming a manager.

Salaries in the field vary widely depending on education level and experience. Hughey says that annual salaries can range from $60,000 at the entry level to more than $100,000 for Ph.D.s. A recent salary survey published by the Commission on Professionals in Science and Technology, using data collected by Abbott, Langer & Associates Inc. for "Compensation of Life Scientists in the United States of America, 2003," reported that the average salary in 2003 for life scientists whose primary area of specialization is bioinformatics was $75,845.

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From the October 13-19, 2004 issue of Metro, Silicon Valley's Weekly Newspaper.

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