Wohlsen: As a reporter who’s covered both biotech and what the rest of the world calls just plain “tech,” I can tell you those stories about biology can be tougher to tell. You don’t have the immediate payoff as much, say, as you’d get when you have, you know, an iPhone with a bigger screen, or when you are able to say, “Apple is really going to make that watch.” But imagine the day that the Steve Jobs of biotech comes on a stage like this and says, “Oh, and one more thing. We’ve cured cancer.” Or, “We’ve solved the energy crisis.” That’s the promise that’s claimed for biology as technology for the 21st century, to solve some of the world’s most intractable problems, to seek truly transformative innovation, and, as we saw some indication of there in that video at a pace that could potentially leave Moore’s Law in the dust.
And so fortunately today we have four people here on this panel who are really on the tip of the spear aimed at that future. We have Nancy Kelley. In the 1980s when the biotech industry was just getting started Nancy was there, and she has had an instrumental role in building it into the industry as we know it today. She is an attorney, an executive, an entrepreneur; she’s helped scientists turn ideas into dozens of companies. She pioneered the practice of life sciences real estate, and most recently is the leader of developing the $1 billion East River Science Park in Manhattan. She has pushed personalize medicine forward as the founding executive director of the New York Genome Center, and she is now at work on a company that’s going to use genomics to perform advanced cancer diagnostics.
We have Floyd Romesberg, whose research really forces us to think the very idea of what we’re talking about when we talk about life. He and his team at Scripps have added an entirely new pair of letters to the DNA alphabet. Instead of just the two that nature created, in Floyd’s lab there are three. Using that discovery they’ve created what Floyd calls a “semi-synthetic organism” that could one day lead to a new kind of living factory.
We have Brian Frezza, he is wedding the digital to the biological in a wave design to bring radical new efficiency to the practice of life science. He’s the co-founder and co-CEO of Emerald Therapeutics, and the chief architect of the Emerald Cloud Lab—and you should see the video of this thing, it’s amazing. The Emerald Cloud Lab basically makes it possible for anyone with a Web browser to remotely perform biological experiments using robots that do all the hard work for you, and they also have an amazing interface that has designed the data that those experiments yield in such a way that really thinks about the user experience as a way to be more efficient at achieving good results.
And last but certainly not least we have Drew Endy. Drew is one of the leading researchers, thinkers, and perhaps the most visible public face for synthetic biology. He helped start the bioengineering majors at both MIT and Stanford, and he really is the leading exponent of teaching a new generation to think about programming life the way that we program computers today. And speaking of computers, his lab has also built a computer out of DNA, and hopefully he’ll talk about that with us today.
So without further ado, the topic of this panel is revolution, “The Revolution Will Be Biologized.” And so I think what we ought to do is we really ought to unpack that notion of revolution, and so I want to throw open to the panel the real basic question of what is the potential here of biology? What can biology really do, what can we expect, what is really going to impact our lives the most? And we’ll start with you, Nancy.
Kelley: So I think all of this kind of emanates from the sequencing of the first human genome, which was completed in 2003 at a cost of $3 billion, and today it takes less than a week and costs $1,000, basically, to sequence an entire genome, which is pretty extraordinary. And that basically gave us the blueprint for what makes life work, and allows us to ask a lot of questions about the world around us and how we can improve it using that information. And so with genomics scientists and doctors are now looking at human genomes and finding where the variations from a reference genome occurs, and figuring out how that causes disease, and then how to intervene in order to cure disease.
And on the cancer front we can actually sequence a cancer right now, figure out what is the variant causing that cancer, target the therapeutic—are they off-label in some cases—drug that’s going to help that patient, and in some cases with really sick people put them into remission for a long time.
Wohlsen: Floyd, how would you answer that question about the potential of biology? What really excites you, what are you anticipating?
Romesberg: What I’m excited about—I’m not trained personally as a biologist, I’m a chemist, and so what I’m excited about is the application with other technologies that chemistry—
Audience: The mike’s not working.
Romesberg: Okay, so I’m a chemist, and so what I’m most excited about is the possibility, the potential of applying things like chemistry to biological problems, and the target being cells and the manipulation and the control and the understanding of biological function, but from approaches that have been traditionally more physically rigorous, more physical chemistry, sort of more chemical, and the application of synthetic components, sort of a chemist’s approach to biological problems.
Frezza: Is it the same question to me, or—?
Wohlsen: Yeah, yeah. No, I’m really interested in getting everybody to sort of, you know, give us your vision. I mean, what excites you the most about not just biology right now, but about its potential. What are some of the big problems that you think, given the capabilities and the capabilities that are being built, that you think we’ll be able to solve?
Frezza: Yeah. I think—I mean, I’m excited about technology in general. I live in this interface between computational—and I was also trained as a chemist as well, actually at Scripps—but—
Romesberg: Brian actually did a rotation in my lab.
Frezza: [LAUGHS] We know each other. But my feeling is—and quite obviously it’s, like, tautology, right? That biotechnology is working on biology, and one of the most interesting problems of our day is certainly human health. It’s one of those things that you can try to impact with other technologies, but you are always indirectly connected, as opposed to biotechnology, which has this very direct, very real impact for the health of all of us.
Wohlsen: Well, now, Drew, we want to talk about health care and the biomedical potential of biological sciences, but your work deals with really kind of expanding beyond what I think is this traditional expectation for what we can do in life sciences.
Endy: What did we get really good at over the last 70 years as engineers or technologists? What are some of the legacies we have of the last two generations of technology? We have hardware, electrical hardware; we have software on top of that, and so you sort of pivot forward in time—what’s going to be the next 70 years? And if you’ve got hardware and software it’s wetware comes next, and when you think about biology as a technology you have it for medicine, you have it for manufacturing, you have it for basically everything our civilization depends upon. And as DuPont might describe—well, there’s biogeochemistry too, right? So you know, we’re sort of at the snowflake at the tip of the iceberg when it comes to biotech.
So you want to talk manufacturing? I live in Menlo Park, the garden clippings in Menlo Park are 500 pounds per person per year. There are 32,000 citizens, that’s 16 million pounds of garden clippings a year compiled from the atmosphere, to a first approximation. And what do we do with this state of the art nanotechnology? We throw it out. Right? As an engineer—“Wow, what could I manufacture with 16 million pounds of nanotechnology?” Locally that’s enough matter to make the computing chips the world uses on an annual basis. How do we do it? We have to make living matter programmable, we have to merge hardware, software, and wetware all together.
You think about medicine, that’s fine too, but think about the movie “Fantastic Voyage” with Raquel Welch. You know, a great movie where you got a clot—inoperable—you got to get the submarine in there with the doctors miniaturized to treat it. The only problem with that fiction is the physicists haven’t shown up with the shrinking rays, so we need an already pre-shrunk submarine—that’s called a cell—and we need to be able to program it. And so you know, just go on and on and on, right?
So how do we make living matter fully programmable or fully engineerable? What would that mean? It’s not obvious exactly what the path will be, but we now know it’s not impossible to make true, and it happens within the context of an existing economy, right? So genetic engineering invented in part in California 40 years ago is already 2 percent to 3 percent of our economy domestically, in terms of annual product revenues. And so if that’s just the beginning how do we keep going forward? And part of that is to imagine what you can do with programmable living matter.
Wohlsen: And so in a sense you are thinking about biology as an information technology, and Floyd, you and I have talked about that a little bit in terms of your work, where by adding that extra base pair you—I think you used the phrase “information density”—you’ve increased the information density that a biological system can use. Can you talk about the significance of that and how it relates to Drew’s notion of programmable life?
Romesberg: Sure. So I think there are a couple ways to think about it. So just to be clear—what my lab has done, as you mentioned, we’ve developed a third base pair between a fifth and a sixth letter, and I think there’s a lot of really exciting stuff—and I think Drew just talked about this—about rewriting, using natural genetics to rewrite what cells are programmed to do. And so with a third base pair there are a couple things you can do. Number one—you could just increase the information density. If you have a 2-bit versus a 3-bit code the mathematics is such that if you, within a given sequence, you can encode more information. I don’t think—personally for me that’s not the most exciting thing. What’s exciting to me is stepping outside of what the information that biology uses—which is all tied up, it’s all tied up in certain things that cells do—and it would be very exciting to then be able to get the cells to step outside of that, and within all of the things that biology allows, things like evolution, be able to direct cells to produce things that you want them to produce, to take advantage of that evolutionary process in the lab, but to be able to do that with information that is beyond what’s encoded currently. And that has potential applications for everything from materials to drugs.
And so what I think is most exciting is stepping into genomes and expanding their potential to store and retrieve information in ways that biology never intended, but which we find very useful for this revolution that we’re all talking about.
Wohlsen: What can you say about—can you say a little bit more about some of the potential applications?
Romesberg: Sure. That’s a very hard question, and I’ll take the remaining 22 minutes if that’s okay. [LAUGHTER] I think everyone here is familiar with proteins—and proteins do everything a cell—they are really what the cell uses to get things done, and there’s been a revolution in medicine in the past ten or so years where we’re now using protein therapeutics to do what people designed small molecules to do before. But proteins have what—they have all these properties that make them really useful and really developable as drugs, but they are extraordinarily limited in the fact that they only have a very few number of chemical moieties that are associated with them. And so if you could get proteins within cells and within those evolution processes, but they are not—but they have chemical protein that is outside of the potential that is there already, you could get them to do new things that the natural proteins never could do. So that would be an example of using the new information and retrieving it in a way that’s sort of outside of biology but within biological systems, but that expand the potential of what the systems can do—in this case proteins to untargetable—against diseases that have been traditionally difficult to drug, and supplying them with new chemistries, new functionalities that are more along the lines of what we think are interesting or useful.
Wohlsen: So it’s life but better.
Wohlsen: [LAUGHS] Brian, on this theme again of biology as information, or the coming together of biology and information, talk about your notion of the wet lab as a kind of Amazon Web services, or you know, talk about how being able to offer the kind of service that you do in this remote way, how that kind of enables a more efficient practice of biology to advance some of these goals.
Frezza: Yeah, sure. That’s sort of a more infrastructure approach. It’s like one layer back from everything that the exciting stuff that, like, Floyd is doing. It’s actually carrying out the experiments in the lab to play out the big ideas like Drew and Floyd have. And in that case you can think of it as biotechnology and chemistry, but it’s really familiarity with lab, and if you look at the makeup of our team you can see that we’re all basically post-docs. We are lab rats who are trying to get all of the machinery in a way that’s accessible to fewer people, so you can sit with a group and you don’t have to manage 25 people, you don’t have to manage millions of dollars’ worth of infrastructure to carry out the experiments, to play out all these fantastic ideas that are floating around out there.
Wohlsen: So would you say it’s kind of a freeing up of creativity, because you don’t have to spend all your time doing the grunt work? Is that—?
Frezza: Yeah, that’s certainly the romantic portion of it, is about freeing creativity. And then there’s the sort of bare bones, hard knocks thing, which is just reducing cost for everybody so that the whole thing can become way more inexpensive. Because you are not paying—it’s a very effective way to share, essentially, a piece of equipment, is to put it on the Web and then set up a queue where the thing is just running constantly, as opposed to signups, which is how we do it in traditional labs—and that kind of thing.
Endy: One way we think about that on campus is the undergraduates want to be able to start biotechnology companies for $10,000. Right? So how do you access the capital equipment you need to do that? And you have to have it through a Web interface with concentration of resources, you know, so it’s hugely important.
Wohlsen: And Nancy, I’m hoping you can comment on this, because—I mean, especially given how much of the evolution of the industry you’ve observed, and you know, your familiarity with the problems of infrastructure, the challenges of being able to get the infrastructure you need to scale, how does all of this look to you given that context? Where are we in terms of being able to get to a company that you can start for $10,000?
Kelley: Yeah, so I think the question of infrastructure is a critical one. The way that we work and the way that institutions interact together has to be different in order to enable in a lab a democratization of science, which is exactly what they’re talking about. And so let’s take the New York Genome Center just as an example. You know, there are 11 founding institutions there. Of those 11 institutions when we started that project, they have 29 sequencers, some of which were older than 12 years old, you know? Compare that to more than 300 that the Broad alone had in Boston. And they realized—these institutions realized that they needed to come together and create this technological center that they could all leverage in order to really serve this incredibly diverse population in New York City, both clinically and in the development of new therapeutics and diagnostics.
Similarly, like in the company that I’m working on right now, an advanced diagnostic testing company, it is very expensive to set up the sequencing operation to be able to do that. It is very expensive to build the laboratory around that, recruit the bioinformatics professionals to interpret that data, build the systems to store the data and access it, and then share it, and it’s going to take more than one institution to do that. But if they all collaborate to do that, then it’s available to any scientist or doctor that wants to use it, and that’s where the real power comes in.
Wohlsen: And you know, Drew, I know that you’re seen by some in the DIY community, which was represented in the video we saw, as a kind of leader, as a kind of patron saint of the idea of making biology more accessible to more people, to the point that, you know, these institutional confines for performing biology won’t be necessary. I want to throw open the question to you first, and then to everyone: how much potential do you see for real breakthroughs from nontraditional practitioners of biotech? What do you see as the potential for people working in this sort of fabled garage environment to actually achieve innovation in the way that Homebrew Computer Club did back in the 1970s?
Endy: Yeah, I didn’t know how to think about this until recently. In 2003 we started a course at MIT where we were inspired by Lynn Conway’s work on VLSI electronics, where in the 1970s coming out of Xerox Park she figured out how to separate the design of computer chips from their manufacture—decouple design, in fact, like an architect designs a building, somebody else builds a building—do that for computer chips. And with that idea in engineering and biology, we wanted to separate the design of DNA sequences from the manufactured DNA sequences.
And we learned how to do that. We didn’t get it right, but we learned how to do that, and that became this thing called iGEM—the International Genetically Engineered Machines competition. We had 16 students in 2003. On Monday of last week there were 4,000 participants at iGEM, and 2500 of them when to the Hynes Convention Center in Boston to showcase their work.
Wohlsen: And these are typically undergraduates.
Endy: Undergraduates, high school students, sometimes they are called over-graduates if they have a few graduate students.
Well, when iGEM started ramping up geometrically, one of the things we didn’t anticipate was where do the alumni go? And some of the alumni would go back to institutions, and the institutions had no clue what was going on in terms of engineering and biology, and so they would leave and graduate and they would have to do something extra-institutional—BioCurious, Genspace, DIYbio, all these wonderful things—but we didn’t really know how to think about it. Is it like the Homebrew Computing Club? And part of me as a technologist was going, “Uh-uh [no].” Because when Homebrew computing got going we had already militarized electronics for decades, right? I mean, Texas Instruments used to be an oil discovery company until World War II, and then they deployed the same technology for setting waves down into the materials and collecting their reflections to not figure out how to drill but to find submarines, right? And from that point forward we have so much core investment in the tech platforms for electronics that by the time the ‘70s come around the personal computer—right?—can begin to be plausible. Consumer electronics can emerge in a much more interesting way beyond transistor radios. And that hasn’t happened. Like, thank goodness we haven’t militarized biology with the post-modern tools of genetic engineering. Let’s not do that. But we haven’t had the economic investment yet.
So some time goes by, some time goes by—all of a sudden it’s changing, and I’m so stupid for not encouraging this even more directly. I work at Stanford most of the time, and when people work in an extra-institutional context in a garage, are they good or bad? Are they garagistas—right?—or are they entrepreneurs? And if I’m at Stanford, jeez, I have to be celebrating the garagistas, because it’s Bill and Dave and Larry, and it just goes on and one and on. This is how we live and thrive. So we can’t turn the extra-institutional actors in biotech into the enemy. We have to figure out how to just make it awesome.
Last week I went to a garage in Palo Alto. There was a hardware startup coming back from Shenzhen. They are called OpenTrons. They are doing the opposite end of the spectrum in many respects from Emerald—they are trying to enable everybody to automate where they’re working when they do biotech. And they had their prototype, they are undercutting the laboratory automation business by orders of magnitude in terms of cost, and it’s just fantastic. So, “Please come into the lab, please give us this and that.” And all of a sudden I’m seeing really this shift in—“We don’t know what to make of them, they are just sort of folks who don’t have a home,” to now they‘re actually becoming the engine of the toolkit. And it’s fantastic.
Wohlsen: You know, there is an interesting sort of dynamic at this conference I feel like, between optimism and realism, and as we talk about the promise of biology and biotechnology, you know, we talk about food, we talk about energy, we talk about medicine and we talk about manufacturing. We even talk about construction. If we look at biology as the technology that will enable us to effect really meaningful transformations in all of these areas, I would just love to throw open to everybody—how optimistic can we be? What do we have to be realistic about?
Endy: Ninety terawatts of power through photosynthesis. That 5x what our civilization runs on, so if you just want to juice things with energy, photosynthesis is pretty good. We can’t take all of that because obviously need to defend the natural ecosystems, and if you are a would-be engineer in biology, if you’re not a frontline defender of natural biodiversity, you are a moron, you’re just an idiot, because we need all the gizmos from nature to do this stuff, right? But when you talk about promise, we do have a capacity to make things on a scale that’s at least matched to our civilization.
If I return to the panel and some comments opening from Reid before, who is responsible for this? Right? There’s that saying, you know, “If you don’t answer the rudder, you’ll answer the rock.” And we’re so afraid of biotechnology in particular, from a cultural-political sense that we’re simply not steering very well. And that has to really change. If you want to talk about promise or peril, the number one peril is cultural-political dysfunction. It’s simply not okay to say, “I’m going to make the engineering and biology much, much easier, geometrically easier. I’m going to realize Moore’s Law.” Right? Because that mostly triggers a freak-out, for good reasons. All right? But so somehow we have to navigate that. That, I think, is the ultimate risk here. I’d reprise some of the earlier comments.
Kelley: I actually think that there’s a tremendous amount of potential and promise right now. Working with Drew and some of his colleagues we just completed a survey, and we interviewed over 110 people in synthetic biology throughout the country in all of the different sectors, and we reviewed about 500 different articles, and the economics of what was actually just started being created in the early 2000s is now being applied to industry in a whole host of ways. You’ve had a four-fold increase in the types of companies that are coming out of this science just in the last three years, most of them in the United States, and by the year 2016 this is probably going to be a $12 billion-a-year industry, and it’s just getting started, so there’s a lot of promise.
Frezza: I just wanted to say—Floyd, you may not agree with this—but the counterpoint to—and it’s weird to be saying this as someone who is trying to democratize, basically, access to equipment—but one of the things that we were just talking about backstage is this concept that I think people get a little wrapped up in: the sense that there should be, like, a Mark Zuckerberg of biotechnology is a very, very good thing, and we should always invite outsiders in. But it’s important to recognize just as much that solving the problems of the practitioners that are already here is a really important thing. So like in Emerald’s case, for instance, we work as much with biotech startups as we do with folks in academia who are quite established as we do with large pharmaceutical companies who are trying to do this more effectively on a giant scale. I think everyone along the pipeline has infrastructure, issues that can be aided for all of us.
Wohlsen: Can you just share real quick what you told me about Andy Grove and how he addressed that?
Frezza: Yeah. That was an interesting talk. So Andy Grove gave this talk that I was very enamored with at Berkeley a few years ago, and he was talking about the differences in health care versus semiconductor industry. And his example—he was talking about how a focus on infrastructure and focus on sort of—we call it—it’s like the first derivative of the problem, the rate behind the work that you are doing is the most important thing if you want to create—a Moore’s Law–like growth curve. So he had this quote about Moore’s Law not being automatic, that everyone had to work extremely hard to make it work. And when they were doing it they were focused on enabling technologies in the fab itself, so if you think about, like, the epitaxial process, the planar process, even integrated circuits themselves, they are all production methods to make it much cheaper to make a circuit.
And then he drew as sort of a counter-comparison to biotechnology, he said, “Take a look at one of your assays,” and he had something that was like a blood panel analyzer or something traditional like that, and over a 50-year period it’s completely flat. And he’s like, “That’s where you need to focus. As much as it’s not interesting in terms of the most exciting research that’s going on, it’s very hard disciplined work on lowering the cost exponentially there that gives progress.” And I think there are these two great—I mean, we talk about it a lot, whenever we talk about beating Moore’s Law, we are talking specifically about sequencing and synthesis. Those are the two technologies that have killed it in those aspects.
And if you even think about the titles of the projects that those are, for the grants, they are things like, “The $10,000 Genome,” and “The $1,000 Genome.” Right? We’re—now at the saying of “the tenth of a cent” or “the hundredth of a cent” western blot, right? Because it doesn’t sound as exciting to be doing stuff like that, but that’s just as transformative in terms of being able to get your work done, if, you know, the funding required—I don’t know, it would be hard to—this is not a hard statement to disagree with—but if it was an order of magnitude less for everyone up here to do all of the wonderful things they are doing, they would certainly be able to do more of it.
Wohlsen: So I want to make sure we have time to get the audience in here. Any anxieties that tinkering with the basic building blocks of life evoke? Any concerns?
Surowiecki: James Surowiecki from The New Yorker. And yeah, I wondered, Drew, if you could elaborate a little bit on—you said there were good reasons—and I have to confess that as I’m listening to you I’m freaking out a little bit at the thought of 19-year-old boys deciding, you know, what they are going to be doing with creating new creatures, or whatever it is they are going to be doing. And I think actually I’m wondering what your—what you think the right response to the kind of political and cultural concerns you raised is, because I do think that this raises—I mean, as we’ve seen just in the reaction to GM food, which is a much simpler issue I think in a lot of ways than this one—this clearly raises a lot of really profound issues for people, and I’m wondering both what you think the good reasons to be concerned about it are and what you think the right response should be from I guess you all.
Endy: A great question, thanks for that. And I think you have to respond by not trying to lump everything together, right? You have to take different topics and examples and concerns as they come, and then at occasion maybe go meta. But so to maybe give you a few and then the rest for offline for everybody to work on—let’s talk about safety, right? So how do we make sure that when people—most of whom we don’t know—engineer living systems they are safe with respect to themselves. They are safe with respect to their family, their local community. They are safe with respect to the environment and other things we might care about. Traditionally a topic of safety is a topic that can be addressed to be a strong community and via education. And if you unpack that one more level timing and leadership here is hugely important. South of here in 1975 at Pacific Grove Asilomar the scientists who invented genetic engineering had conversations to think about the safety of that. People who had that leadership position in 1975 are higher up in age now, and so we’re in the biosafety renewal period where we have a moment in time to pass up a time, both of practice and leadership in biosafety.
Take a different topic—biosecurity, right? You have the safety belt in your car, but you have the security lock on the door, because you can’t always rely on the intentions of others who might be mal-intentioned. What’s our plan for biosecurity? What’s our plan for biosecurity in a world where we get incrementally better at understanding living systems and tinkering with them and—guess what? We don’t have one. We mostly don’t have one for interesting reasons. We shut down the offensive weapons program during Nixon. The bioweapons program. So that means the security professionals mostly don’t understand bio—mostly. The biomedical research enterprise correctly diagnoses that nature is already running a bioterror program—it’s called natural flu. I have 30 people my age die in San Francisco last year from the flu.
So how do we bring together a public health enterprise with a security professional network and do something that’s not reactive, right? When we have on order of 30 casualties of anthrax in ’01, you have a 10x increase in the civilian biodefense budget that in large part goes to create more semi-classified biosafety level 4 facilities which apparently was the source of the anthrax attack, right? That seems like a political-cultural autoimmune response.
So there’s not one answer, because the topics are super complicated. You’ve got topics like safety, you’ve got topics like security, you’ve got topics like equity. Not stock equity, but fairness, right? You’ve got topics like—“Hm, how do I feel about the—I actually don’t like GM food, why would I want modified food?” I want engineered food, you know? So how do I begin to talk about that? And on and on and on.
So at a meta level, you know, what I wish for is a capacity to have cultural leadership, collectively. Maybe we can do it in different ways. But it’s very hard to even frame let alone sustain the discussions on these topics, they typically freeze in some type of dysfunction, and then stuff just goes.
Wohlsen: I think we have time for one more. Over here.
Zelikow: Philip Zelikow from the Markle Foundation and the University of Virginia. I’m a former dean at my university. The number one obstacle to hiring lab scientists in the university is the startup costs, in that it’s not salary, the issue is every time you hire a lab scientist you have to set aside millions of dollars to build their lab. So you are making a powerful case here for deeply different ways to think about addressing the startup costs for hiring new scientists. So I’m asking myself—and then want to ask you—let’s talk about the business model for a moment. Universities right now are cumulatively spending billions of dollars on building many, many labs, and Nancy gave an example of just what kind of proliferation she encountered as a result of that. And actually a lot of those labs then aren’t state-of-the-art a few years later. They hire a new biologist, he says, “Well, I need my own lab, I can’t use that old lab equipment, it doesn’t do my experiments.” So let’s talk a little bit about whether instead of the NSF essentially funding some of that process, the NSF at a modest fraction of its costs might actually fund public goods infrastructure. It seems like we have a collective action problem, that if the universities pooled together fractions of the amount of money they now spend—the NSF, the NIH—put that money into it, we could actually unleash much more biology at a fraction of the cost. Am I right?
Kelley: Actually, when we completed the strategic plan for the synthetic biology community in the U.S. that was one of our conclusions. Each of the universities that are currently the leaders in working in this right now—Harvard, MIT, Stanford, UCSF, Berkeley—they all have built tremendous infrastructure at their universities which are used primarily by their own scientists. And what we were arguing is that we need as a country to invest in that same kind of infrastructure that would be available to scientists all over the country, to be able to use to carry out their own experiments, you know, and really facilitate the democratization of science in this area.
Frezza: Yeah, and I would say, obviously that’s something we think very strongly about, and that is exactly the—you should come talk to me afterwards, because I’d very much like to get it to the point where you are not having to reinvent the wheel and buy all that infrastructure again. So for us we charge per experiment. You are paying no more than a couple bucks per experiment, and you don’t have to buy millions of dollars’ worth of lab equipment to get started, and that’s exactly the problem we were trying to address, is that startup capital.
Kelley: The other thing is that the way science is done is changing enormously right now. So you know, traditionally it’s been a principle investigator who is a senior scientist with a lot of post-docs in the lab working underneath that scientist. And that’s changing right now, so you are seeing experiments which are done in a distributed manner all over the world, and the data collected an shared between scientists, rather than, you know, being kept confidential until publication. So things are changing, people are beginning to work in very different ways, and I think it’s going to transform the physical environment in which science is done.
Wohlsen: So unfortunately the red light is telling me that’s all we have time for, but I want to just give a great big thanks to our panelists, and hopefully we can keep this discussion going.