Kim de Mora
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Here There (Will) Be Dragons: Beyond the Map of Synbio with Kim de Mora

It’s almost safe to say that if at any point in your scientific career you’ve been involved with synthetic biology, then you have been impacted by Kim de Mora’s work. An engineer-turned-scientist and passionate educator, Kim served six years as Director of Development for iGEM, the International Genetically Engineered Machine Competition, one of the biggest funnels of synthetic biology enthusiasts worldwide.

Kim is both collected and explosive. Talking to him feels like fast forwarding through the history of synthetic biology as a whole. In our interview, he speaks about the work he has just wrapped up with iGEM, as well as what’s coming next for him in his new role at Addgene.

There isn’t much need for me to talk after the initial question rolls out.  So I put my student hat on, and I listen.


“iGEM is a non-profit educational foundation that teaches how to program DNA to high school and undergrad students.” Kim pitches quickly before moving on to what was one of his main jobs during his tenure: the growth of iGEM and its mission, in every sense of the word. He tells me that iGEM has around 310 teams worldwide, and compares it with the amount of teams that participate in the First Robotics Championship: a whopping 6,500 teams.

“You need a certain amount of resources in order to be able to do [synthetic biology].” he says, referring to what iGEM teams need to get started. “We’re not quite at the stage where you can just pick up some tools in your garage and do this – there are enthusiasts that have done that, yes, but it’s still a bit hard. You can’t just go out and make a synbio project as you would more easily with teams in robotics competitions, for example. A lot of those teams operate out of diesel mechanic shops, so you’ll have a small, rural farming town where they don’t have an academic institution but they have a diesel supply or a repair shop, and for a robotics championship being able to weld and build things for everything except for the AI, you can find a lot of that stuff in the shops.”

There’s still this difficulty in being able to start an iGEM team, in some respects, but Kim knows that the effort is definitely worth it considering what students get out of the experience.

“iGEM is great in a lot of respects, students learn an awful lot. A longtime iGEM PI, Frank Sargent, said iGEM is a mini research career in a summer, because you have to come up with an original idea, you have to raise money, you have to test your hypothesis and advance your work and engineering, and you have to communicate your science to an audience of your peers. And you know, if you’re going to be a researcher, here you get to do this at an undergraduate level, whereas currently you may get to second, third, or fourth year pHD before you get to have that experience. So that’s a really good way of thinking about it. And if you have a grad student running the team, that grad student gets to feel what it’s like to run a lab for the summer as well.”

But it’s far from an isolated individual experience. As Kim emphasizes, iGEM is real science as a team. “That is very rare in academia,” he expands, “fundamentally because of the way science is incentivized. If you look at what matters in science (especially in most fields of biological sciences), effectively it’s first name and last name (on the publication). That’s what ties the big research dollars, the grants, the Nobel prizes and all that. There are very, very few initiatives where scientists are rewarded as a team even when you get to cancer and heart disease research for example. Science is still incentivized as an individual activity, not as teamwork. If you compare that to engineering, you have a bunch of engineers in a company trying to build a computer or a car or a plane, and the goal at the end of the day is to get that product out the door, and everyone is incentivized by the success of the collective project itself, not by having their names printed as first or last name.”

It’s a video-less Skype call, but I can practically see Kim beaming. “iGEM is like that. It’s the team that wins, not an individual student. And so one of the things so powerful is the amount you can achieve when you work on a scientific problem as a team. I think in that respect, we are actually way ahead of a lot of ways in which science is done, because of the fundamental incentivization behind it being a team project. And so, students coming in, their first experience with synthetic biology through iGEM isn’t just about iGEM and science, it’s about science as a team, and that leaves a lot of students with this longing to continue that afterwards because it’s very hard to get back to this. Like, you don’t do science as a team as a PhD student or as a postdoc, so one of the really powerful things that iGEM is doing is changing some of that culture.”


Kim tells me that according to Clayton Christensen, author of “The Innovator’s Dilemma,” half of the universities of the US are going to fail in the next ten to fifteen years. As a global tendency, this begs the question: what will happen to teaching and training of science?

“If you look at computer science” says Kim, “there are a lot of things you can do online. You can probably learn most of what you need and demonstrate what you know to get a job programming maybe without ever having gone to college. Collegiate level of degree doesn’t always correlate to performance of the employee, according to internal Google data.”

“However, in biosciences, you need a bench. And if colleges start to go away, then where does that come from? So for 4, 5 years I’ve been trying to convince the DIY community guys that they need to be ready to step in with training for biosciences: offer modules, interface with things like Khan Academy and Udemy and give online bio courses. Because the power of online tuition is that, as opposed to having a teacher, you can have the best teacher. And if you can get the best teacher, or the one that teaches to your style of understanding, then you have a much higher chance of being able to learn. So you need both the material that caters to your learning style, and then the wetlab space where you go and learn the hands-on skills.”

Going back to the robotics competition and the 6,000 teams, this seems to be the way to get there: “Not by convincing every university in the world to have a team, but through new educational models where this is fundamentally a stepping stone to a career in the synthetic biology industry. I see education in synthetic biology going in that direction, that’d be the new lean model for bio education for the next 10, 15, maybe 20 years. And what do you do when you have a bunch of enthusiastic young students that have taken all these modules?”

A small, expecting pause.

“Well”, he laughs. “They do iGEM.”


As the conversation progresses, Kim keeps the comparison going between building biology and building robotics or software, drawing from his extensive experience and previous life as a mechanical engineer. When I ask him about the future his education ideal describes, the comparison comes in handy again.

“There’s a lot of technology and infrastructure development that needs to happen so that we can get to that world. Using the coding analogy, you sit in a café, and if you’re really good you can put out a website or an app really quickly, but that’s because you can type a bunch of code in, click a button and compile your code, execute it and run it in your laptop. We’re not in that position in bio. We’re still at that stage where NASA was with programming in the 1960s – winding wire around alternating magnets to create ones and zeroes.”

“With companies like Emerald and Transcriptic, though, we are eventually moving forward to a word where you’d be able to build your bioscience company in a café, click a button, and then your experiment will run automatically on a robot thousands of miles away. But we’re not quite there yet. And the use case for individuals building companies doing that sort of thing isn’t quite there yet. From my understanding, most of Transcriptic’s business is pharma assays with higher paying customers, not startups.”

But tech moves forward and becomes cheaper and we do seem to be moving in the right direction. “So it will go that way eventually,” he remarks, “but there are some intermediary steps. Moving forward, the job of a PhD student won’t be to pipette tiny volumes of clear liquid into other tiny volumes of clear liquid. It will be to feed the robot. Feed the robot at 5, push a button, come back in, feed the robot again in the morning, and then you concentrate in data analysis… as opposed to liquid transfer.”


When we delve into futurist and precognitive questions, Kim reminds me that the key to making predictions is having an understanding of exponential scales. And the computing analogy strikes back.

He tells me about his mentor, Randy Rettberg, who was “one of those guys who was on the internet when there were only twelve computers there. He’s one of the guys that built the internet, the one that developed the first switch that connected the first dozen of computers, and he wrote the first TCP/IP protocol for Unix in the early 1970s.” He stops briefly, maybe wondering if he lost me with the computing lingo. “If you typed faster than 10 characters per second, it couldn’t keep up.” He laughs. “He was one of the guys that saw that.”

“One of the interesting things about that story,” Kim says, “is that I asked them two questions: What did you think was going to happen [regarding the internet], and did you predict any of the stuff that we have now? The answer to the first one was, We all knew it was going to work. We all knew computers and the internet were going to be a big deal – 45 years ago they knew that. That is the same feeling I have for synthetic biology.”

“The other question was, did you predict things like Twitter and social media? The answer to that was a resounding No. They did not predict that most of the internet was going to be about allowing people to share pictures of cats with each other. So that’s the thing: What’s the killer app for synthetic biology? What’s the killer move that’s going to take synthetic biology from being this pharma thing to everyone’s thing? What’s the smartphone application of synthetic biology?”

He continues to elaborate: “In twenty or thirty years we might look back and go oh god, it was obvious, but now, looking forward, it’s hard. I think that there are a number of synthetic biology applications that will be focused on human health and longevity, and if you think of a bacterium as a drug that has onboard computation and sensing capabilities, then you can achieve a lot with that. If you can actually build a sophisticated enough system that’s well-programmed enough, that doesn’t have a high degree of evolutionary drift, so you can have sensors that will detect cancer or extracellular proteins or particular information in the brain in early stages of Alzheimer’s’ or stuff like that – and I know there are people that are already working on that sort of thing, but there’s a big difference between an interesting science paper and an engineering population deployment-ready product. That’s the big difference between science and engineering: Science seems to study this phenomenon while engineering seeks to make use of it.”

He stops himself and sighs.

“But that’s one of the obvious ones. That’s like if you’re in the 50s in the computer world saying mass storage will be a thing. That’s obvious. But if we want to go for the weird thing, the twitter, the social media and sharing cat videos of synthetic biology, then who knows?

It takes maybe three seconds where I’m hard-pressed to think about something that’s not a cat meme drawn in luminescent bacteria for Kim to show me that he’s in a whole other level.

“For example: Here’s all the ingredients you need to grow your own dragon! Do you want it to have big wings? Little wings? Do you want the fire to be blue or yellow? For ages 5 and over. I mean, I don’t know!”


Technology will keep moving forward and yes, computer science may feel like they hit a wall right now – a physical limitation wall regarding the physical space available for transistors, but they will find a new way of solving this, be this 3D chips or quantum bits or whatever, and their evolution and improvement will continue. Which is why Kim doesn’t think biotech will replace what computers technologies do.

“It’s unlikely that there’d be a cellular version of Twitter. Bio, in it’s single-cell level, is very compact and very good at sensing and making molecules, so maybe some of the killer things moving on will be home manufacturing instead.”

“One of the key concepts of the Singularity is technological convergence. There will be a point where two exponential technologies will cross paths. For example, 3D printing and synthetic biology – what do we get there? Instead of printing organs, maybe we might be able to make all sorts of interesting materials at home that you can use to manufacture things. You can maybe start getting into co-manufacturing of plastics and rubbers and all sorts of things, maybe with living materials.”

“So, I think that if you look at the pharma industry relative to the consumer market, for example, the latter is orders of magnitude bigger. So it’s interesting to look at companies like Biopop, Ecovative, Bolt Threads, Ginkgo Bioworks, Modern Meadow. Because you’re starting to have consumer applications of synthetic biology. With these things, you always start with the low hanging fruit: in this case, single cell organisms that do simple things. You have to start with that before you can have the Grow Your Own Dragon At Home kit. And you move on.”

But way before growing dragons in our garden, there are steps that synthetic biology needs to overcome. For Kim, one of the main ones is the same hurdle that circuit simulation technologies solved for engineering: simulate first, check if it works, and only if it does, you build it.

“We don’t have that kind of technology right now with synthetic biology. You order DNA from someone and you have a one base pair deletion that causes a frameshift, well, I guess you can alter it, but you can’t just order this thing and make it work. You may end up with mistakes that require redoing the whole thing – same as the computer chip manufacturing or airplane building and engineering and everything did before full simulation – I can’t give you a piece of DNA and you give me the exact confirmation of the protein, we can’t do that yet. That’s one of the big things that’s holding the industry back, because there’s been a massive amount of investment, $1.7B according to you guys, almost double from 2016…” a pause. “but that’s probably still less than what people spend in phone cases. Engineers in the phone industry probably spend more than that on coffee.”

(The world is expected to spend $107.3B in phone accessories by 2022. Out of that, around 36% is estimated to be phone cases. So we are looking at about $38.6B spent in phone cases, slightly over our $1.7B synthetic biology investment. I have yet to find reliable sources for the coffee consumed in the phone industry figure.)

“My point is,” Kim continues, “It sounds big, but we’re still a small industry. Small and important and growing, yes, and looking at that 2016 to 2017 double of investment, but we’re not at the point where we have major companies manufacturing stuff that everybody needs.”  

Even so, Kim stays optimistic about the future that synthetic biology continues to build.

“I’m really hopeful for the future of synthetic biology. I think it’s like being in the computer industry in the 1970s or 1980s. Everybody knows it’s going to be a big deal, that what we’re going to do is changing the world. I think it’s looking very bright, and it’s going to be a very interesting time for the next decade or so. And having been in synthetic biology for twelve years I remember a time when nobody said it would work. The professors all said there’s no chance, you’re just teasing the students, you’re just wasting their time. And today, iGEM has 300 teams and the industry has $1.7B investment.”

It definitely looks like we’re getting somewhere. Don’t take it from me, but from someone who has been there during the growth of synthetic biology from a stage arguably earlier than his mentor and the twelve computers on the internet – a nice rhyme in history to cement Kim de Mora’s place in the story of synthetic biology.

This interview was conducted in January 2018.

Emilia Díaz

Emilia Díaz

Best described as an entrepreneur, writer and speaker, Emilia is a young Chilean innovator working in the intersection of science and social impact, hoping to make the world a better place through biotechnology. At 22 she founded Kaitek Labs, one of Chile’s most renowned synthetic biology startups, for which she won numerous prizes, raised public and private capital, and attended business programs in Europe, Asia and Silicon Valley. After 4 years of writing about global biotech in various outlets and seeing the lack of Latin representation in the global scope, she also founded Allbiotech: the first Latin American Biotech network for biotech. She seeks to grow the local ecosystem through scicomm and innovation.

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