Alnylam Pharmaceuticals, Inc. (ALNY) Earnings Call Transcript & Summary

John, thanks for being here with me today to chat about your success in Alnylam.

Thank you, Jen. I do want to start by saying if Ginkgo can make it easier, I would love that because it wasn't easy to what we did. So it's an opportunity, for sure.

I would say a lot of people in the audience today probably have aspirations to do exactly what you did, which is to take a new therapeutic modality and bring it to market in a wildly successful way. So I'm curious to learn kind of what were some of the big decisions that you made along the way to address the kind of compounding risk, right? In drug development, you're trying to manage between biology risk, a new modality risk, regulatory risk, clinical risk and so on. How did you manage that risk through the process?

So the story of managing that risk at Alnylam is actually quite interesting. So at one level, we had to figure out where we can achieve delivery of small interfering RNA and then really focus on that cell type and that tissue for developing our human therapeutics. But then around 2010, we crafted a strategy that we called Alnylam 5x15 that really tried to optimize our overall likelihood of technical success with this new modality. And so what we did is we focused on targets expressed in the liver, where there was human genetic data supporting the target either in loss of function or gain of function, human mutations, then we also required any target that we would pursue to have a biomarker that we can measure early in clinical development so we can remove the traditional pharmacology risk inherent in doing drug development. And then, of course, we wanted to have targets and indications where there were definable endpoints from an approval standpoint and value definition perspective. So that amalgamation of criteria turned out to be a really smart thing to do because it reduced our biological and clinical risk as asymptotically close to 0 as we could possibly do. And of course, we kept technology risk with our new modality that we had to optimize. But at least we remove the biology risk as much as possible. So that approach, that decision and that strategy really turned out to be a very wise move. And I think a lesson that can be used with other modalities and platforms that are out there as well.

And by the time you got to the 5x15 strategy, you said been working on the modality for some time. So did you have some sort of assessment or thought process you went through to decide that the modality was ready?

Yes. We had to really spend about a decade trying to optimize the modality, trying to figure out how to chemically modify these RNAs so that they weren't stimulating immune responses. We had to figure out informatic-based approaches to basically achieve selectivity of the molecules we were creating. But the biggest thing we had to do is figure out how to achieve delivery of these small interfering RNAs, which are really not that small from a drug standpoint. They're 14,000 daltons. And so they're not engineered to get inside the cell. And so we really had to figure out different approaches. And we ultimately ended up with 2 different strategies for delivery. One was to use lipid nanoparticles, like the ones that we've all used in our mRNA vaccines. And we sort of helped pioneer the use of those lipid nanoparticles for delivering RNA. And then the second technology that we use that frankly, ended up being more robust for us was using a chemical conjugate to the sRNA that enabled delivery to a cell type through a receptor-ligand interaction and a very rational approach in enabled subcutaneous delivery of these small interfering RNAs, but it also enabled a remarkable durability of pharmacology for these agents as well. And that was something which we didn't anticipate until we started generating animal and then human data.

And when you were tackling sort of the delivery challenges, you gave 2 specific examples that you ended up using, but I understand you are starting to look at many, many delivery methods, -- how did you sort of think about looking at the scale of those or the expansion of them? And how did you narrow that down over time?

Well, I think one of the ways you have to think about a platform technology of a new modality is a bit like an hour glass. So you start wide, then you figure out where you can build your pipeline so you go very narrow and focused. And then at the end, if you're successful with that, you can then go broad again. And so that's exactly what we did in our journey at Alnylam. We had at the beginning, a very wide-ranging set of technologies that we would evaluate to figure out how to achieve delivery, to figure out where we could ultimately build our pipeline. Once we figure that out, once we identified the liver and hepatocytes as being attractable cell type and tissue, we focused and we focus very, very clearly on many pipeline opportunities so we can engineer in the liver. But then more recently, we were able to then expand our efforts again and go after things like CNS delivery of RNAi therapeutics or other extrahepatic tissue like muscle, for example. And so that our glass like approach that we took is something which I think is applicable for any modality that's out there. Certainly, what's being done to some extent with gene editing technologies right now using ex vivo-based approaches followed by in vivo-based approaches. It's a wise approach because you ultimately have to find the low-hanging fruit and really try to make medicines out of those low-hanging fruit opportunities as sort of your first mission.

Yes. So speaking of the low-hanging fruit, you had an interesting sort of story around this -- I like the analogy of ringing the bell, so the sort of Jingle Bells you hear before Santa Claus comes as sort of helping people in the market, stay the course with you. Tell us a little bit about that story and how you help show the low-hanging fruit to keep people on the bigger course.

Well, the story of RNA interference is very similar to other technology stories that we all read about in business journals and business textbooks. The period of excitement followed by a period of despair and lack of enthusiasm followed by ultimately, if you're successful, value creation on the other side. And in the middle, when we were in our despair moment as a technology, it was extremely clear to me that the only way we could really convince investors to stay the course with us was to generate human clinical data. And I use the analogy, if those of you with children may know the children's book the Polar Express, with the little jingle bell and the kid that can hear the jingle bell and he's able to believe in Santa Claus because he hears the bell, but his mother and father and older sister can no longer hear the bell. And I use that analogy with my kids were young at the time. And so I used that analogy with my team to basically emphasize that no matter what data we were showing early on, people weren't hearing the bells. People weren't believing what we were seeing in animals. They needed to really see it in humans to really believe that we can do it. And so it was about bell-ringing during those days. I had a bell scale slide where on the left-hand side, it was a jingle bell. On the right-hand side, it was the Liberty Bell and a big one. And so we would track where we were in our progress in terms of generating human data, but ultimately, we got to the big bell.

Yes. Amazing. Coming back to this hour glass picture you painted for us of going big and then narrowing and then going out again for the platform. It's very similar to a chart that Jason showed in his keynote speech, thinking about sort of the conundrum, let's say, of improving the platform while advancing the pipeline, right? At the beginning, you need a lot of R&D, then you kind of go into clinical and focus, and then you want to ramp, back up. Did you experience that at Alnylam? And how would you advise people to approach that same sort of sinusoidal curve?

Yes. It's a fascinating challenge in building a company like an Alnylam where you -- again, you start needing a very broad research effort around your platform. And then when you finally figure out where you can build your development programs, you need to focus, but also as part of that focusing invariably, you realize you've got to preserve your balance sheet to invest in the clinical development side of it. And so in 2010 and then a second time in early 2012, we had to do 2 restructurings of our workforce to basically change the complexion of our workforce to enable more space in our balance sheet for doing development. And horribly tough thing to do to let your colleagues go and let a good number of them go. But if you can find a way to variablize components of research early on so that you're not having to go through that dynamic process, it would be terrific. We have ways of variablizing some of our development workforce with CROs that are out there for clinical trials or manufacturing, but there isn't as much on the research side. And so if there were a way to keep that variable with external technologies and capabilities, that would be very valuable because you would never have to unfortunately let people go from your team.

So thinking about the use of CROs or external innovators, maybe we can kind of close out with like how should pharma companies think about open innovation, the use of platform companies, when to think about going external and when should you work in-house? And what would be your advice for them?

Well, I think there's an enormous need to embrace precompetitive technologies in a very open way. And there are many, many capabilities, technologies that really should be shared very openly across the biopharmaceutical industry. And it ranges from genetic data to different technologies, whether it's delivery technologies, where companies need to create the intellectual property to ultimately defend their asset comes down to where they have composition of matter on their drug candidate, and that's where they have to defend it. But everything up until then really can be shared in a much more open and precompetitive manner. And I think there really is an opportunity for the pharmaceutical discovery process to have common elements that can be shared across companies and with a common technology provider in a very open way. So I would welcome that type of opportunity for companies to have access to those technologies.

Yes. I hope so. Any last advice you'd give to people in the audience who are building new modalities?

Well, I'll close with a quote from George Bernard Shaw which I think is applicable to anybody who is developing a novel platform technology. The quote goes along the lines of this. "The reasonable man adapts himself to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable man." And so I think to do a modality, a novel modality, you have to just be outright, unreasonable in what you're doing. And I think that's the best advice I can give you from my experience. So thank you.

Wise words. Thank you so much.