CURT NICKISCH: Welcome to the HBR IdeaCast from Harvard Business Review. I’m Curt Nickisch.
At the beginning of 2020, hardly anyone had heard of the biotech company in Cambridge, Massachusetts called Moderna Therapeutics. It was ten years old and did not have a single commercial product.
By the end of the year, Moderna was selling millions and millions of doses of one of the most effective Covid-19 vaccines in the world. That commercial product not come from a eureka moment or a stroke of luck in the lab. That vaccine based on cutting-edge messenger-RNA technology was the product of a repeatable process. It’s been used countless times by the company that founded Moderna: a venture creation firm called Flagship Pioneering.
Here to talk about how to systematically make breakthrough innovations in unexplored domains is Noubar Afeyan. He’s the cofounder and chair of Moderna and the founder and CEO of Flagship Pioneering. With Harvard Business School professor Gary Pisano, Afeyan wrote the HBR article “What Evolution Can Teach Us About Innovation.” Noubar it’s so great to have you.
NOUBAR AFEYAN: Great to be here.
CURT NICKISCH: You were a biotech entrepreneur even before you founded Flagship Pioneering, which is this innovation and venture investment firm with the goal of systematizing breakthrough innovations. From your experience as an innovator, what’s wrong with how people think about breakthrough innovations?
NOUBAR AFEYAN: Well, certainly innovation drives the whole technology startup world. And so everybody’s after innovation. But over the 20 years or so that I’ve been involved in doing this type of work before Flagship, what I had come to observe is that the kind of innovations people are working on end up being really focused on adjacencies.
The whole notion of an adjacency is something that is a logical extension of what’s been done in any number of different directions, but that’s something that people can then assess how likely is it to work? How valuable might it be? And over time, it occurred to me that the reason they’re able to do that is because it’s pretty proximal. You could pretty much see it.
And while that makes a lot of sense, and I’ll point out that the way funding happens, whether it’s from the NIH for the research side of the innovation or incumbents in their in-house innovation efforts or venture capital that largely funds startups, all three categories basically assessed the degree of value based on whether experts or key opinion leaders, validate the idea.
Which by definition means it’s adjacent, because it will be hard to imagine how an expert could foresee what 10 years from now might become valuable. But they’re going to be very authoritative about things that are here and now.
The problem with that is that it’d be hard to imagine that breakthroughs are that close in. And so there’s a real challenge, how do you make breakthroughs happen when your process favors things that are very proximal? And that’s what led us to thinking about, “Could there be another way of making breakthroughs happen and, by definition, move further away from the here and now?”
CURT NICKISCH: I mean I’ve heard of incremental innovations described as better, faster, cheaper, and breakthrough innovations as brave new world. Is it like changing your thinking as much as that?
NOUBAR AFEYAN: What I would suggest is that our cognitive skills are pretty good at extrapolating in a way where if you can just think of one step or two steps beyond you have a fairly good sense of what that might be. But then when we think about things that are completely disconnected with the current reality, what we refer to as a discontinuity, then we need our imagination, which is something that I’d say, even though scientists and engineers have as much creativity potential as an architect or an artist, nevertheless, in our day-to-day work, we’re somewhat guided away from that because we’re supposed to be grounded in the truth. And when it looks like it’s a step or two removed from the current reality, it seems speculative. It seems a fantasy and therefore non-scientific.
It’s almost like I think there’s a gravitational field around idea spaces that keeps forcing us back to the here and now, because it’s grounded, it’s reasonable and other people will validate us. And the question is, “Can you escape that field?”
CURT NICKISCH: Yeah. Well, messenger RNA, the technology on which Moderna’s vaccine, the COVID-19 vaccine, is based might be a good example, right? The scientists who first worked on that had a hard time getting their articles published. And now looking back, some of those folks may eventually earn Nobel Prizes for it. But it was hard to gain acceptance at first.
NOUBAR AFEYAN: And that’s the story we hear over and over again in just about any field that ends up in a disruptive application, because once it happens, we go backwards and we look at the early beginnings, but with a fresh perspective of what eventually happened.
Now the mRNA case is an interesting one because people have studied mRNA, described mRNA, which is a natural molecule. The natural version of mRNA has been fairly well elucidated and people have won lots of Nobel Prizes for that, but the use of mRNA as a synthetic construct to deliver information was, in fact, very early on in the eighties already viewed to be problematic because when you introduce an mRNA molecule into a cell, it was observed that you would essentially cause a reaction similar to the way cells react to viruses, an antiviral reaction. So the cell basically thinks it’s being invaded.
That’s kind of where the field stood. And years later, already in the nineties, scientists at UPenn and a couple of other places started modifying RNA, particularly mRNA, to try to see if they could understand what is the mechanism of that immune response.
But the ultimate use of it as a therapeutic was not an immediate adjacency at the time. And it’s only if you want to use it as a therapeutic that all these things take on a very different appearance, because now they become things that need to be enabled towards an end goal, which in our case, when we started our journey, really was to say, “Could we deliver a molecule to the patient or to a subject wherein their own cells could make any protein of interest?”
Well, to do that, which is a completely imagined goal, you come back and look at what the science told us, and all the work suddenly gains a different relevance. And so when we saw some of this work, we said, “Okay, well, if there’s three, four modifications that have been suggested, could we try 100? If there are ways to deliver it to cells that have been tried but were somewhat problematic, toxic, could we try a whole lot of new ways to deliver?” So these things gain a different purpose and that purpose recasts the science in a very different way once you develop your own new goal.
CURT NICKISCH: It’s almost like a Blue Ocean Strategy for biotech innovation. It’s finding a place where there is probably a lot of value. But you’re a pioneer in that space essentially figuring out where to go?
NOUBAR AFEYAN: You know, what I describe it as is you can either work today on what’s next and then the future is defined by whatever it actually succeeds, or you can try to aim for something in the future that is disconnected with reality today, but then you come back towards and you pull the present forward into that vision that you have.
They’re just opposite forces. One is a push to what’s next. The other is a pull of what we know so that you can add the pieces you need to get to where you want to get to. And the pioneering nature of it is really to be willing to make in the first instance the leap, mental leap first, then combined with a group of people, a community leap, making sure you get a lot of people thinking about the same space and saying, “Is there a reason to believe? What’s missing in making this happen?” And then you set out to actually build that future. That’s the way we think about making breakthroughs. And if you said, “Well, why should that lead to breakthroughs?”
The answer is it doesn’t always lead to breakthroughs, but by definition it leads to completely unanticipated things, because from the present, just about everything you work on that’s far enough removed is not computable, is not reasonable. And once you make it real, people kind of find it surprising. And that’s part of the effect of a breakthrough.
CURT NICKISCH: Does it take different kinds of people? Do you have to hire different kinds of scientists to think differently? Or is it about managing the very same scientists who would be successful at a university, in a lab, managing them differently for this kind of forward process?
NOUBAR AFEYAN: Well, the flippant answer to that is yes, and then some. So both of those, and then more. So first of all, I don’t believe it is kind of an innate issue, you’re born with it, you’re not born with it. In general, I think that this is a capability that a lot of scientists can have, provided they allow themselves to a little bit depart from the rigorous constraints of what the scientific fields they’re in may impose.
And it turns out what we do, and what we’ve done now for 11 years in our existence, is we first found that we need to create our own fellowship program and literally bring in graduate students within a year of graduating, or MDs within a year of graduating and have them immerse themselves for a summer fellowship and learn how to do this.
And among the things that we do as kind of almost shock therapy in the beginning of this is to actually ask these folks to say unreasonable things comfortably, meaning not kind of filter themselves. So it’s really interesting when you talk to people and you say, “What’s the last unreasonable thing you said in your field, something that you knew was crazy, but you said it anyway?” And it turns out it happens very relatively rarely. The more successful people are, the more rare it is.
But that uninhibited state is what I think you need to be willing to explore in order to then discover unforeseen possibilities. So some of that can be experientially learned, but listen, for some people, this feels totally uncomfortable. And it’s not for everybody, that’s for sure, but there’s a lot more people who we’ve seen over the years thrive in the ability to both leap and do rigorous science in the space they’ve lept to than what they believed coming in.
CURT NICKISCH: How do you as a manager or as a leader of one of these organizataions, how do you create a climate where people feel like they can say unreasonable things?
NOUBAR AFEYAN: As a leader, you can’t expect people to persistently say unreasonable things if you’re not willing to say unreasonable things, or laugh at the unreasonable things you’re saying, or admit that some of them turn out to be grossly mistaken.
But as well, it’s what you do or how you react when people do say crazy things. I have a sign behind me at my desk that says, “Trust your crazy ideas.” I’ve had it for 20-some odd years near my desk, because it’s an interesting play on words when it says trust your crazy ideas, because trust is a permission to persist long enough for the crazy idea to be proven to be actually transformative. And if you don’t trust it, then you just won’t have the staying power and you’ll immediately move on to a much safer idea. So there’s an element of that kind of environment where that’s okay.
But look, the other thing is why should people believe, when they’re in this milieu, why should they believe that this could lead to value? And there I would simply point out to the history of major breakthrough innovations, mRNA is no exception, but there are many, many others as well in technology where if you look at what actually became valuable, and you trace backwards to its roots, what you quickly find is that the ancestors of great, beautiful ideas are really ugly things.
And they are totally rejected in the first instance repeatedly. It’s not at all the exception. Every single one. If you go back and look at, for example, the early version of what an iPhone was, it looks nothing like an iPhone. It’s the size of one of these iPad Pro large devices. And if you looked at that, you would never imagine that the descendant of that would be an iPhone as it is today.
So, what is the lesson in that? The lesson in that is trying to actually conceive of these beautiful things out of the gates is a waste of time, because they’re never the ancestors of eventually a disruptive thing.
So, I at least have a belief that there is this process of emergence, which we call emergent discovery, but there’s a process of emergence that describes the evolution of ideas, for that matter scientific ideas or political ideas or religious ideas, that this emergence of variation and selection happening in iterative cycles produces an end result that you’re surprised derived from the original starting point.
So, that same idea is what we have used here as we’ve created an emergent culture where people don’t look for beauty out of the gate. They don’t look for reasonableness. They actually are comfortable creating otherwise, I’m saying this for shock value, ugly looking things. Provided that they then don’t stop there, but they use that as a starting point to iterate, iterate, iterate until the descendants come about that start gaining more and more reality or value. And only those descendants are the things we end up working on. I don’t know if this made sense, but that’s the way I describe it.
CURT NICKISCH: What are the biggest obstacles, the biggest stumbling blocks to that process reaching a great result?
NOUBAR AFEYAN: Well, first and foremost, looking for affirmation from others. Ironically it is the case that if what we’re working on is viewed by others to be a really good idea and really reasonable, we shouldn’t be working on it. Because at the end of the day, it’s only a matter of time before it becomes a commodity.
I once in a while Google the notion of commodity innovation, because people think how could you have a commodity innovation? But to me, an innovation that’s available when it’s made can be remade by lots of different people is going to be a commodity innovation. Shared economy is a commodity innovation. Right? Everybody can now go around and rent their houses. So, there are different factors that lead people to win in that space.
But we don’t want to be in commodity innovation. We want to be at an innovation that is as protectable and as different from the commodity space.
CURT NICKISCH: Yeah, one of the things you mentioned in the article is that the great thing about working on a nonadjacent space like this is that you can patent everything as you go and own that space.
NOUBAR AFEYAN: Definitely the case. Also, you can create the whole scaffolding for the space because you can create the rules of engagement. You can describe the field. You’ll be first to know where the landmines are. You’ll be first to know with mRNA what causes it to go to certain tissues and not others. You’ll be the first to know that when you give it to a non-human primate model, a monkey, that it works very differently than a mouse that others don’t know because they’ve never been there.
And so, there’s a there’s advantages to being someplace first that if… and patents are an important enduring version of that. But there are many others that you might say, “Boy, why doesn’t everybody do that?” And it’s because the list of disadvantages is much, much longer.
The reason pioneers are often unsuccessful is because it’s a lot easier to do things in a connected, rational way. But also you have other people to emulate. You have people giving you feedback. You have all sorts of services that help you do what you can do today. None of those exist for the future. Right? There’s no supply chain for an unimagined product. Imagine in mRNA, the whole world got to witness last year that we went from having produced enough mRNA to dose 2,000 patients prior to the arrival of COVID to now enough mRNA to those 200 million patients. The supply industry needed to make mRNA, in all regards, did not exist at the beginning of 2020. Zero.
Now it took a heroic effort, both at Moderna as well our colleagues at Pfizer, but also at the U.S. government level with Operation Warp Speed, to do the unthinkable, which was to literally organize 7,000 different companies like in a wartime, a brand new industry. Namely not the mRNA industry, but the mRNA supply chain industry. In normal times that would’ve never happened. That’s another advantage of working on current things instead of unprecedented things.
So, there’s lots of reasons not to do this. But the exciting reason to do it, which I want to emphasize, is that you’re basically discovering new value pools. So, this notion of a value reservoir which awaits us, that’s what innovation is, is innovation is opening up value pools. You’re either opening up new little corners of the current value pools, or you’re going into completely unprecedented pools of value. Imagine a natural resource that you’ve discovered, some new important mineral that you found or whatever. If you’re willing to leap and reach to well beyond the adjacencies, turns out to be the real driving force.
And coming back to your question, there’s a lot of ways to make that possible. Among them, interestingly, is examples of say success in doing that, which we’ve accumulated over the years, that encouraged the next generation and the next up to say, “Hey, this can be done. Why can’t we do it? This was just done.”
CURT NICKISCH: Yeah, I found that surprising that Flagship Pioneering is investing in, what, half-a-dozen companies a year, right? These are all potential new value pools that you’re going after. Is there that much white space in non-bio-tech innovation at other companies? I just wonder how much of this works in life sciences and can it apply elsewhere?
NOUBAR AFEYAN: My sense is that where there are scientific advances that lead to value generation, this approach has some interesting additional advantages over the conventional approach to innovation. And I say that, for example, as we’re speaking today, one of the most interesting areas to me of scientific disruptive potential is machine learning and artificial intelligence. Why? Because the generative side of that, not the interpretive side that is looking at patterns from data, large data, but the generative side that can create brand new things that we have not previously created. That generative side is essentially a new source of things that could become valuable. And so how one uses that. So there is a space where we’re putting in quite a lot of effort beyond just life science in that we think this type of emergent discovery as a way to find these valuables could be very powerful. Now, if you’d said, can you do this everywhere? A version of this might be helpful in other aspects of transformation and innovation.
So one of the interesting things that’s happened recently is there’s a lot of large company leadership that I’ve happened to know over the years that have taken interest in what we’re saying and doing and wondered, can we do it? Can we, as a consumer- packaged goods company, can we as an airplane developer, these are real examples, actually say, okay, how would it look if we tried to anticipate five, 10 years out and work backwards in the spaces we’re in.
And I’m going to be interested to find out how some of these approaches may apply now that people are seeing examples of it and they see how there are some parts that could be repeatedly done, that it’s not pure improvisation or a miraculous kind of discovery, but rather hard work.
CURT NICKISCH: Noubar, it’s been great to have you on the show to hear you say some reasonable and unreasonable things. Thanks so much for sharing your knowledge and expertise with us.
NOUBAR AFEYAN: Thanks for having me.
CURT NICKISCH: That’s Noubar Afeyan, co-founder and chair of Moderna Therapeutics and the founder and CEO of Flagship Pioneering. He’s also coauthor of the HBR article, “What Evolution Can Teach Us About Innovation.”
This episode was produced by Mary Dooe. We get technical help from Rob Eckhardt. Adam Buchholz is our audio product manager. Thanks for listening to the HBR IdeaCast. I’m Curt Nickisch. That was great. Yeah. Thank you.
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