Q: Are there any roadblocks to what you can measure and what you can’t?
Sullivan: Will there be laws and technical hurdles to face? Yes. Are we even close to insurmountable barriers? I think the answer is no. When you go into life science, we’re only beginning to understand cell biology. Some people talk about molecular computing. From my perspective, we just have infinite choices. Agilent Labs just introduced the first measurement of micro-RNA, which was only invented five years ago. These structures are in the 10- to 15-nanometer range. I think you’re going to see discovery in the chemical, physical and life science worlds.
Q: How much of your business is coming from life sciences?
Sullivan: The company last year was essentially 70 percent electronic measurement (40 percent of that business was semiconductors before the divestitures) and 30 percent life sciences and chemical analysis.. However, our life sciences/chemical analysis business is the fastest growing part of our business. This year, you’re going to see life sciences becoming a larger percentage of our company. We just completed the acquisition of Strategene, which is a re-agent company that uses chemicals to react with a specimen to try to get better measurement results. Our number one investment and growth opportunity is in the life sciences area. This is a great example of where we can take some of the best analog and digital converters from our electronics expertise and apply it to this market to improve the resolution of the mass spec measurements of, for example, the detection of proteins. How do we take these measurement technologies and move them into these new opportunities? When you think about measurement, we always tend to look at the physical world—measuring a photon, electron or molecule. Our job is to turn it into the digital domain and digitalize it so that engineers, scientists and researchers have a different insight. That’s really where it’s going. About 70 percent of our engineers are software engineers. How do you digitalize it in such a way that they can seen nuances that help them in their discovery?
Q: Isn’t that modeling?
Sullivan: Modeling tends to be a very defined role, such as measuring a radar system or modeling a simulation of a wireless city. This goes further. How do you map out data so that people can see something they wouldn’t have seen consistently with their past models? The future is creating new models, but to do that you have to have the ideas and the concepts from the old models and visualize data so you can create new associations looking forward. That’s what so exciting about life sciences. It’s in its infancy, and it’s an associative science. People are making associations because they don’t have ab solute models about how it works.
Q: Do you see moving into a different role in the future? You are bridging electronics, spectroscopy and massive data searches.
Sullivan: That is the bet of Agilent. Having the breadth of technology, can we bring this technology synergy with our financial strength to differentiate ourselves in this $40 billion measurement market? The market is highly fragmented with lots of different applications. Through an acquisition and through our technical support we’ve entered into the top atomic force microscope market. How do we bring sophisticated, complicated tools to the desk of the scientist at a competitive price to accelerate learning?
Q: We’ve largely been focused in the electronics industry on the atomic level. Is the subatomic level in your sights yet?
Sullivan: We’ve had a big debate about that internally. Nobody has seen it yet, and I don’t know when that will happen. But people are really smart. They will figure it out. The biggest potential is the continued understanding of cell biology and the very sophisticated mechanism of what goes on inside of a cell that results in disease. There’s a tremendous opportunity for us to measure that, visualize it and model it so people can continue making advancements. It’s basically how do you prevent chronic disease earlier in life.
