A Solution Looking for Problems
In the late 1990s, microfluidics (or, as it is sometimes called, “lab on a chip” technology) became another overhyped advance in an era notorious for them. Advocates talked up the potential of the chips. But the devices couldn’t perform the complex fluid manipulations required for many applications. “They were touted as a replacement for everything. That clearly didn’t pan out too well,” says Michael Hunkapiller, a venture capitalist at Alloy Ventures in Palo Alto, CA, who is now investing in several microfluidics startups, including Fluidigm. The technology’s capabilities in the 1990s, he says, “were far less universal than the hype.”
The problem, as Arthur might put it, was that the toolbox was missing key pieces. Prominent among the needed components were valves, which would allow the flow of liquids to be turned on and off at specific spots on the chip. Without valves, you merely have a hose; with valves you can build pumps and begin to think of ways to construct plumbing. The problem was solved in the lab of Stephen Quake, then a professor of applied physics at Caltech and now in the bioengineering department at Stanford. Quake and his Caltech coworkers found a simple way to make valves in microfluidic channels on a polymer slab. Within two years of publishing a paper on the valves, the group had learned how to create a microfluidic chip with thousands of valves and hundreds of reaction chambers. It was the first such chip worthy of being compared to an integrated circuit. The technology was licensed to Fluidigm, which Quake cofounded in 1999.
Meanwhile, other academic labs invented other increasingly complex ways to manipulate liquids in microfluidic devices. The result is a new generation of companies equipped with far more capable technologies. Still, many potential users remain skeptical. Once again, microfluidics finds itself in a familiar phase of technology development. As David Weitz, a physics professor at Harvard and cofounder of several microfluidics companies, explains: “It is a wonderful solution still looking for the best problems.”
There are plenty of possibilities. Biomedical researchers have begun to use microfluidics to look at how individual cells express genes. In one experiment, cancer researchers are using one of Fluidigm’s chips to analyze prostate tumor cells, seeking patterns that would help them select the drugs that will most effectively combat the tumor. Also, Fluidigm has recently introduced a chip designed to grow stem cells in a precisely controlled microenvironment. Currently, when stem cells are grown in the lab, it can be difficult to mimic the chemical conditions in a living animal. But tiny groups of stem cells could be partitioned in sections of a microfluidic chip and bathed in combinations of biochemicals, allowing scientists to optimize their growing conditions.
And microfluidics could make possible cheap and portable diagnostic devices for use in doctor’s offices or even remote clinics. In theory, a sample of, say, blood could be dropped on a microfluidic chip, which would perform the necessary bioassay–identifying a virus, detecting telltale cancer proteins, or finding biochemical signs of a heart attack. But in medical diagnostics as in biomedical research, microfluidics has yet to be widely adopted.
Again, Arthur’s analysis offers an explanation. Users who encounter the new tools must determine whether they are worthwhile. In the case of many diagnostic applications, biologists must better understand which biochemicals to detect in order to develop tests. Meanwhile, those developing microfluidic devices must make the devices easier to use. As Arthur reminds us, the science and technology must build on each other, and technologists must invent the missing pieces that users want; it is a slow, painstaking evolution.
It’s often hard to predict what those missing pieces will be. Hunkapiller recalls the commercialization history of the automated DNA sequencer, a machine that he and his colleagues invented at Caltech and that was commercialized in 1986 at Applied Biosystems. (The machine helped make possible the Human Genome Project.) “Sometimes, it is a strange thing that makes a technology take off,” he says. Automated sequencing didn’t become popular until around 1991 or 1992, he says, when the company introduced a sample preparation kit. Though it wasn’t a particularly impressive technical advance–certainly not on the level of the automated sequencer itself–the kit had an enormous impact because it made it easier to use the machines and led to more reliable results. Suddenly, he recalls, sales boomed: “It wasn’t a big deal to pay $100,000 for a machine anymore.”
In a recent interview, Whitesides demonstrated a microfluidic chip made out of paper in which liquids are wicked through channels to tiny chambers where test reactions are carried out. Then he pulled a new smart phone, still in its plastic wrapping, out of its box. What if, he mused, you could somehow use the phone’s camera to capture the microchip’s data and use its computational power to process the results, instead of relying on bulky dedicated readers? A simple readout on the phone could give the user the information he or she needs. But before that happens, he acknowledged, various other advances will be needed. Indeed, as if reminded of the difficult job ahead, Whitesides quickly slipped the smart phone back into the box.
David Rotman is Editor of Technology Review.