The a16z Show - The Machine That Made the Vaccine: Company, Platform, Innovation

Episode Date: December 21, 2020

In this special episode of Bio Eats World -- which aired right after the FDA authorized Moderna's mRNA vaccine for emergency use -- Moderna CEO Stephane Bancel tells the story of not just the vaccine���s development, but the machine that made the vaccine: the platform, the technology, and the moves behind the vaccine’s development.How does this new technology that uses mRNA work; why is this such a fundamental shift in the world of drug development; and where will this technology go next? https://a16z.com/2020/12/18/moderna-covid-vaccine-mrna-technology/ Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Hi, everyone. I'm sharing our most recent Bio-Eats World episode here because it covers the topic of vaccines, a theme we've covered here since January of this year in our early and ongoing pandemic coverage as part of our mission to continue bringing you everything you need to know about this crisis, as well as how tech changes our future. You can find our past coverage, including early discussions of plug-and-play vaccines, to breaking news and what we still need to know, to how vaccines in general are made, and what was done process-wise to, accelerate development as well as the politics of who gets it first at a6.c.com slash vaccines. But in the discussion that follows, our BioEats World Show, be sure to subscribe if you haven't already, interviews the Moderna CEO, which aired right after the FDA authorized their vaccine for emergency use. And it goes into the machine that made the vaccine, including the machine inside the company and the platform itself. More details in the intro that follows.

Hi, I'm Lauren. And I'm Hannah, and this is BioEats World, our show where we talk about all the ways biology is technology. This week, in place of journal club, we have a very special episode featuring Stefan Bancel, CEO of Moderna, in conversation with you, Hannah, and A16Z general partner Jorge Condé. And we're talking about the COVID-19 vaccine, right? Yep, that's exactly right. The conversation is a really incredible dive into how they developed one of the world's most awaited vaccines. Bancel describes everything from the moment he first realized they could make a COVID-19 vaccine with their technology to the day he heard the first data on how effective it was

in humans. In this episode, which is airing just after the vaccines and related biological products advisory committee meeting makes its recommendation to the FDA, Stefan tells the story of not just how the vaccine got made, but everything about the machine behind this vaccine, the fundamental new platform and MRNA technology behind the vaccine's development. This vaccine is really one of the first medicines that is part of a bigger transformation from a world of pipettes and lab benches to a world of industrialized machines-making medicines. We used to grow our vaccines, but now we can print them, getting them to patients faster and

more efficiently than ever. Bancel describes what it took to go from pathogen to design to clinical-grade product, how MRNA works in a chocolate moose metaphor and what makes it different from old vaccine technology. Why exactly this is such a transformative shift in the world of drug development and where this technology will go next. Stefan, sitting here now in December of 2020,

could you have imagined a year ago that MRNA as a concept would be a household name? No, and we had a lot of things going on in vaccines, in cancer, in autoimmune disease, in cardiology, in reagenetic disease. But I had no idea that 2020 was going to look that way. So if we flash back to January of 2020, can you talk a little bit about the process that you went through to realize that you potentially had the technology that could be a solution for this emerging pandemic?

Yes. So I've been working in infectious disease. all my career, and I've developed an eye for outbreaks. So one of the things I do is I read the Wall Street Journal and the Financial Times every morning as I get up. And between Christmas and New Year of last year, I noticed an article saying that there is a new pathogen agent in China giving pneumonia like symptom. That's all it says. and so I sent an email to somebody working for Tony Fauci,

Barney Graham, who we have been collaborating with four years, designing several vaccines together. And I say, hey, Barney, have you seen the new pathogen in China? What is it? Is it a bacteria? Is it a virus? And you replied to me a few hours later, and he says, it's not a bacteria.

It seems to be a virus, but we don't know which one yet. And the day or two after, Barney sent me an email and say, hey, we learn from our contacts in China. It's not flu, it's not RISV, we don't know what it is yet. And then another day goes by and he says, it's a coronavirus, but it's not SARS and it's not males. It's a new coronavirus. Within a day or two, the sequence should be put online by the Chinese.

And so on January 11, the Chinese put the sequence online. And our team at Moderna used the sequence to design a vaccine. In parallel, Barney's team does the same thing. And when they shared note after around 48 hours, they had designed exactly the same vaccine. A couple of things that are fascinating about this. Number one, the fact that the digital copy of this virus came from China before the biological version reached our shores.

That's remarkable in and of itself, that we knew what we were dealing with, at least digitally, in a matter of days, thanks to all of the advances of genomic sequencing technology. But the other remarkable advancement in technology here is that you just described, you were able to design a vaccine based on the digital version of the virus, also in a matter of days, is it?

So you're right, Rohi. And this is the piece that I think most people in pharma don't appreciate yet the power of a money technology is in 48 hours, we designed and locked down the entire chemical structure of a vaccine. Unbelievable. And we click order on a computer. So it all happened in silicon. we never had access to a physical virus

and we designed the vaccine and we had again the two team at NIH and Moderna because we were so worried to make a mistake in the vaccine design as you can imagine. Of course. So we're super happy when the team literally compared note after two days and that exactly the same design for a vaccine

because it was an outbreak and we knew every day mattered. At the same time we started to make clinical-grade products to go into a phase one. And that's a piece that is really remarkable is the vaccine that is reviewed by the FDA on December 17. It's exactly the same vaccine that our guys designed in January in silico. We never change one atom. It's exactly the same way of you.

So it's the same vaccine that took 48 hours to design. That's going to help hundreds of millions of people next year. Can we take a moment to just get really simple and talk about how you would define this messenger RNA technology and what you wish the public understood about how MRNA works. Right. Yes. So it's a molecule that exists in every one of your cells that is basically the Xerox copy of an instruction of your genome for one gene at a time to make protein in your cells.

So the way I will describe it to my two young daughters is think about DNA like the hard drive of life, where all the instructions. of all your 22,000-ish genes are stalled. And think about it a bit like this is a recipe book that your grandma gave to you before she passed away. All your favorite recipes, that's the hard drive, that's DNA. And when you want to make, let's say, chocolate mousse, if you go with your grandma's precious book into the kitchen,

you're going to damage your book a lot. There's going to be flour and eggs and sugar. And after a few times, you might not be able to read the recipe anymore. So what evolution has done, which is beautiful, is to protect the integrity of the instruction in the hard drive, in the book. When the cells want to make one protein, like let's say insulin, what it does, it makes a copy of the instruction only of insulin in the book, like my example of chocolate mousse, a Xerox copy, and takes it into the kitchen, i.e. the cell, to make through a little machine called the ribosome that I describe as my kid as a little 3D printer that reads the message.

said with the instruction of MRNA and makes a protein by adding one amino acid at a time. So it's a natural molecule that basically carries genetic information to make proteins. But using MRNA as a tool in the way you've been doing it, that was not always an obvious approach. So can you talk a little bit about where that began, that idea, and what it first looked like? Yes, so it's actually very interesting when MRNA and DNA were discovered. world. Actually, people in a lot of universities try to make medicines out of Emane because it

was a very logical use of Emane, just copy nature, make a synthetic Emane injected into animals before humans, and it would make a protein. Because of what was known about science at the time, including immunology, all the analytical tools that did not exist as part of manufacturing, purity, and so on, when they would inject Eamon in animals. animals who live through like symptoms of fever, vomiting, diarrhea. Because MRI, if we remember, most viruses in life, including COVID-19, is made of MRI. And so through evolution, mammals have developed mechanisms to recognize foreign MRIs. And of course, when you inject an amaranne as an idea for a drug, there would be a foreign

amount. And so actually people abandon and just quit on trying to make a marijuana as a drug. What happened in the 2010-2011 time frame here in Boston is you had a set of academic at Harvard and MIT who started to play with MRA again because there's been some new discoveries made in the immune system that they believed at the time that if you modify uridine, which is one of the four letters of MRAN, you can make an MRA that's immunosylent. In some ways, when you think about it, Moderna doesn't make therapies. You make instructions that the cell uses to make its own therapies. Yeah, correct.

We don't give you a vaccine. We give you an instruction for the sales of healthy people in that case to read the instruction, to make one protein of a virus, to make it as well as if they had been infected by the real virus, to show it to the immune system.

So the immune system can make a neutralizing antipers, body and matured so that if later they get infected by the real virus, the system is ready to prevent the virus from multiplicating in their body and getting them sick. What get people sick in infectious disease is you have too many copies of a virus. Yeah, and so I think this is a remarkable thing for a couple of reasons. What you're essentially doing is you've looked at the virus's genome and you've said, okay, if I take certain pieces of code from this virus and encode that, them in MRNA and deliver them to human cells, I am basically given the human cells the instructions

to make pieces of the virus that the immune system will train itself on, recognize, and eventually neutralize. And in this particular case, that target was the spike protein in the SARS-CoV-2 virus. Is that accurate? That's 100% correct for it. And the reason that MRNA, in my opinion, is so powerful is that you totally mimic. to a human cell, the natural biology of an infection, without giving the virus at any time.

We never give a virus to people. We give, as we said, a piece of a virus. In the case of corona, because it's a pretty simple virus, we believed, and the clinical data have shown in the phase three that we were correct, that one protein of a virus, a very important one, the spike protein, if you were able to get a high quality of a high quantity of neutralizing antibodies,

you should be protecting people if it become infected with a real virus. Why is it better to have the cell mimic this natural process than in the old technology? And that's a piece that is really unique because when you think about it, when you get an infection by an amyone virus in your body, what happens?

The virus of an RNA gets in your cell. You use your own cell machinery to make the protein to basically self-replicate inside your cell. And then he escaped your cell and this is what your immune system sees. And so if you think about it, the old technology of vaccine, where you make in a E. coli cell or a true cell, a protein that then you inject in a human and that just circulate in your blood,

that is not mimicking the natural biology. In our case, the spike protein, we designed the vaccine, so it's made inside the cell, so in a human cell, not in an E. coli cell. And then we designed it to be transmembrane, to stay attached to the cell and to be presented to the immune system that basically patrols in your blood, your body, and we'll see that thing sticking out of a cell that is not self. If you think about the 3D configuration of a B-cell coming onto that protein,

it is exactly like if it was a natural infection, which is why if you look at the data across the nine vaccine we put in the clinic, the antibody level is so high because it's perfectly mimicking nature. How did you know which protein and that one was enough? How did that process work? That's a very good question. And as Mr. Pastor would say, and of course there's a big role in his vaccinology, only the prepared mind.

So one of the thing we were doing with Dr. Fauci's team for the last couple years is we are collaborating on studying viruses that could become outbreaks. None of us thought we will see our lifetime a global pandemic. The last one, we are all aware of us, students of infectious disease, of course, the Spanish flow. And so one other thing where we got lucky is we had been working for a few years together with Dr. Falkchishy's as part of that project for outbreak readiness on the MERS vaccine, the Middle East respiratory syndrome, which if I had used those words a year ago, nobody would have known

what I was talking about. But today, everybody knows it's another coronavirus. us. We wanted to provide to them MRI for research grade, so animal testing, antigen design, picking the protein that makes sense. Because Marni is so easy to make once you industrialize it, we were able to send to NIH to the team working on MERS, all the different vaccine design they wanted to try in animals. They will vaccinate the animals and then they will challenge by giving them, you know, high dose of a virus. The one that was the most protective

was always a spike protein. They tried a lot of combination, but spike by itself was always the best. The theory, I assume, is because you're essentially putting neutralizing antibodies around the spike, and the spike is what the virus uses to get into cells in the first place. Correct. The full-length spike

protein was always the best. Some companies went into a clinic with three, four, five candidates. And there were different hypotheses. They were test. We didn't have to do that because we had tried it for Campolioles. We knew that with our MRI, our best guess, was going after full-length spike protein. At a very high level, you are essentially printing these vaccines versus growing versions of a virus or a denatured virus.

So you can design it, you can print it, and then you can obviously get this into people very quickly as a result. that is a remarkable part of this entire story that is probably somewhat underappreciated that allowed you and collectively us to move so quickly. When did you know, Stefan, that, all right, this is going to work. This is going to work for COVID. I had a very high belief

that this should work since the beginning. So since January. Because this was the 10th vaccine we were working on. So I've seen the human data of a previous one. And the infectious disease, unlike in oncology, where the animal models tells you nothing. The infectious disease, if you look at a lot of data, there's extremely high translation from animals into humans. I saw Mars data before we started, of course, dosing in human. So I knew the data in mice looks great.

So because with the nine vaccines before, I know it was going to look great in human, which we learned all of us in May. Can you describe, Stefan, when you first, first saw the interim phase three data and what your reaction was? So it was a Sunday in November. I knew the independent NIH-led safety data monitoring board was going to meet at 10 a.m. on Sunday. And so I told my wife and my kids, I'm going to be a wreck the whole morning. I tried to pretend to work, but I was so distracted. I will check my email every two minutes, my phone every two minutes for a text message and so on,

maybe a bit before one. I got a text from my team saying, hey, get on a WebEx. We're going to get the data. There was not even a slide made. It was just somebody talking and literally reading towards the data. And so I learned about the close to 95% efficacy.

It was already a big N, and the P value was very, very low. Very, very low. So this was real. And the piece that was almost the most exciting to me and my team was the severe case of disease, which there were, I think,

eight or nine on the interim data. We have now 30 on the final analysis. And there was zero on the vaccine. They were all on placebo. And you think about what this means when you connect those two data set together. It means if you get our vaccine, you have a 95% chance of having

zero symptoms if you get infected by the virus. You will not even know you are sick. You just go live your normal life. Zero symptom. And in a 5% case where you will get disease, it will be mild disease. You will get no severe disease. When you think about what has happened to our society, the elderly, people who high comorbidity

from hospitalization when it gets back leads to death and the total impact on the economy, the loss of jobs in so many industries and so on, that whole cascade. If you could have a vaccine where most people, 95% get no symptoms, and the 5% we do get mild symptoms, never go and walk into a hospital, that would be a total game changer. So listen to the data and we talked to my team a few minutes. I don't think we were processing. And then I left my home office and I called my wife. She was in the house.

And I told her, and I just started crying in the house. I think that's what it felt like for all of us hearing it too. It felt like, you know, normal life could return. It was the promise of something like that. We are losing right now 3,000 people in this country. I think it's more than 10,000 people a day around the world. And it's going to be a very tough winter. And that's only the human toll, which is gigantic.

But the piece I don't think he's talked about enough is mental health toll happening to people at every age. All the young in especially, you know, more disfavored communities where, you know, people are living in a small apartment where mom is trying to work. And kids are trying without a computer or without a good internet line to learn remotely. The impact this will be going to have in terms of equality. And then, of course, so many industries have been totally destroyed. I mean, look, they are closing, you know, indoor dining again, which I think is the right thing to do. Because I think the most dangerous thing right now is to have dinner indoor. I have not worked into a restaurant indoors since March, and I won't go until I'm vaccinated.

So as amazing as I think the COVID vaccine story is, I think it's also worth talking about the machine that made the vaccine, the technology platform that you have built over the course of 10 years that allowed you in January 2020 to say, like, hey, we need to develop a COVID vaccine. I remember coming to visit Moderna and Kendall Square, that first facility you had. And what was interesting about it is when you walked in, it didn't look like your typical biotech company. It was a row of machines, a row of printers, a row of robots. And that's very different than what your traditional biotech company looks like. And it looked a lot more like an assembly line in some ways, where you can order something up and out the other end would come the MRNA medicine that you had ordered.

Yes, and this goes back to this incredible property of MRNA, which I'm surprised that so many have missed, is that this is an information-carrying molecule that you can industrialize. When you are in an analog business, which is what I think old pharma and old biotech is in my book, is because every molecule is a different chemical entity, you cannot industrialize the making of a lot of it at the research grade. You have to literally have chemists in pipettes and so on, doing like we all building chemistry class,

writing the synthetic route to get to a molecule that they want to do the biological effect they want. And then they have to design that chemical equation and then all the pipette and test tubes to do that. And when it's another molecule, they have to invent another synthetic route. So it's really an analog world where you invent every, thing once at a time for one product. Because if every product is different,

you have to re-optimize every time. And sometimes it's very complicated because of a very complex biological system. So sometimes it will take you six months, 12 months, 18 months to get ready from preclinical data to be making clinical grade product that you need to file to FDA so that they give you the green light to go into testing this inhuman. It's a highly regulated, as it should be. be processed to protect people's safety. But in our case, it's always the same thing.

Because Amanda is always made of four same letters, the four letters of life, like zero than one in software. It's the same manufacturing process. This is like software or Lego. This is an engineering problem. It's an engineering technology. It's a platform. The only difference between all Zika vaccine or all CMV vaccine and the COVID vaccine, it's only

the order of a letter, the zero than one. of life. The manufacturing process is the same. The equipment is the same with the same operators. It's the same thing. And so this is why we could go so fast. It took us 60 days to go from a sequence of a virus person like by the Chinese to dosing a human. The first SARS-COV-1, or as he was known before, SARS, he took the NIH 20 months to go from sequence to starting a phase one study. So you went from 20 months to two months. Which is remarkable. Are we in the plug and play future for vaccines? Oh, 100%. We're going after making a seasonal flu vaccine, because as we know, still, you know, 10,000 Americans die every year on average of seasonal flu.

We believe that we should be able to make a big debt on two flu. And today we know we have six vaccine in development. We're going to have many more soon. Because for 10 years, No, Rore, we hoped that MRA-N-A vaccines were going to work. We believe scientifically they were going to work, but until you have a phase-free, randomized placebo-control study where you test really prevention of disease, you don't know. Now we know. Are there limits right now to how sophisticated these instructions can get,

or can we essentially give them as sophisticated instructions as, you know, the human body is capable of? It's when the mechanism of a disease is not well understood. So we spoke about vaccine and we said, look, coronavirus, as I said, is actually a simple virus. We as a society got lucky. Think about HIV. HIV has been discovered 40 years ago. They still, to this day, no approved vaccine against HIV.

Think about the awful world we will be in right now. If Dr. Fauci will be standing on the presidential podium back in the spring. and told them, folks, I'm sorry to tell you, but this is an awfully complex virus. We have no idea when we might have a vaccine. Think about the state of mind we will all be in now. The biology of rare genetic disease is very well understood. Why?

Because kids got too bad genetic information from their parents that they cannot make a correct protein. And that is what caused their disease. They have a wrong instruction in their DNA. If you can get them an MRI from all technology, coming in their cells with the right instruction, then they will have the right protein and they won't get sick. If you think about cancer, on the other hand, of a spectrum or Alzheimer now,

if the disease mechanism is not understood, we cannot drug it easily. We can try things, of course. We could make an amount of the biopolis, go try it in the clinic, but a lot of things will fail because you are guessing. And so the piece where I think we have an incredible tailwind, basically overlaps doing academic biology work around the world are helping us. Because if tomorrow there is a paper published by a lab in the US or in China or anywhere in the world

that says protein X, Y, Z is the root cause of that disease or those five proteins in this ratio are the root cause of that disease, then we can literally turn on a computer and in our design a drug to go test that hypothesis in an animal. Basically, the power of this approach works when you know what you want to make and then you just need to deliver the instructions to make that. Where it doesn't work as well is when you're not quite sure what it is that you need to make. This is basically biology complexity or biology risk. The other dimension for us is the ability to deliver the MRN in the right cell. We actually have become a delivery of nucleic acid company.

we realize that what would allow us to maximize the impact we could have on disease for helping as many people as we can over the next five, 10, 20 years is the ability to bring a M RNA to different cell type. So a good example today is if you say, look, there is this university that published the mechanism of Alzheimer's disease. If it happens in the brain and we don't know how to bring M RNA in the brain safely, we cannot drug it. So the biology will be understood,

but the delivery technology will not be there. An example where we're making a lot of progress right now is the lung. We have been working with vertex around how to deliver MRNA via an aerosol via your mouth into your lung because they know the biology very well. And we work together to develop a delivery system to bring MRA safely into your lungs

and to bring enough MRA at a safe dose. to get the biological effect. And we're getting very close now. Once we can prove in the clinic that that delivery system work, then the next morning you can make any other drug you want that you need to get into the lung. Because it's getting another set of zeros and ones, coded differently with the same delivery system into the lung.

And that's the power of the technology, which is why with vaccines we're able to go so fast. The instructions have gotten so sophisticated over time that now the next sort of horizon is you've got to get the vehicle for delivery equally sophisticated. We're adding vertical after vertical after vertical. They bring MRN into a new cell type. So the vaccine is one vertical. Getting MRI into a tumor is another vertical.

We have a very cool drug where we inject MRI in people's heart after a heart attack. And here we code for a protein called VEGF, for a biology geek on the podcast, VEGF, That is a protein that we all have instruction in our DNA, which basically tells your body to make a new blood vessel. Amazing. You use that protein every time you cut yourself. Stefan, you've mentioned, you know, kind of the fast design of the vaccine, and then you mentioned even robots printing medicines. Can we get your version of what that machine assembly line looks like? So the robotics farm we have in our factory is basically just a number.

assembly of robots that get instruction coming directly from computers. There's no human interaction. And basically, you start from a piece of DNA that is basically your template. You put that in a reactor with water. There is no cell. It's a cell-free manufacturing process, which is why it's so fast. And you put enzymes. And basically, what the enzymes do, they attach to the DNA and they read the DNA template. And they put little pieces of nucleic acid, i.e. the zeros and ones, the four letters of life. They bind them next to whichever to make an mRNA molecule. Then the robot goes to the next step,

which is you add a cap, thing about it, like the nose of a molecule, that you add again with another enzyme. Then what you do, you purify the MRI. So basically you pick the mRNA from all that water, enzyme, and nucleotide, nucleic acid, and so on. And then when you have a pure MRI

molecule after purification, you mix it with a lipid, i.e. fat. And that fat basically goes around and package like in a little bowl, the MRNA, to protect the MRN in your blood and to get the MRI inside your cells. When it's inside your cells, the lipid, the fat falls apart. The mRNA is released inside the cell.

And the little ribosome, the little free-day printer of your cell is going to read that message, make the protein on demand, and here you go. The patient, the human, is making his or her own medicine. I remember from the earliest days, you were obsessed with the operations. You were obsessed with turnaround time, with throughput, with cost per output. And the benefit of that approach is that it obviously is compounded over time. The benefit of the technology, as you're describing it, is that you have a machine that prints the instructions that go into the cell that uses the cell's machine to make the medicine or to make the vaccine. And that's this incredibly powerful paradigm, you know, to taking therapeutics or vaccines from being very bespoke efforts to being truly industrialized, designed efforts.

That's what it's really so powerful, is that the whole drug process is all about information. The piece that is remarkable is you have this very modular technology because what happened in our cell is actually extremely logical. We start from the sequence information of a virus, like in the case of a COVID vaccine. Or we use the human genome. We put into a technology genetic-based cassette. And then you click literally order on the computer and you go again. And that's the vision I always had since the day one. And a lot of even of my scientists at the beginning thought I was crazy.

Because this industrialized, engineer-driven approach to drug discovery has never happened. So, Stefan, you've described this process, which is much more efficient, industrialized in nature. incredibly fast compared to the old process. Is there a world in which that gets even faster? Are there other things, other increases in technology that would speed this up even more? Yes. So it took us 42 days to go from sequence

to shipping the human great vials to Dr. Farci's team. The big bottleneck is sterility testing, a very important quality control test that is done for any injectable privacy call to make sure that there is no bacteria in the product. That test takes two weeks, because what basically you do, you take a sample of your vaccine and you wait enough time if there is only one copy of bacteria,

the time you have enough multiplication of bacteria to the detection of the assay of the test, that you will see it and you will not miss it. It's very important for people's safety. Well, if there was a technology developed where you could do sterity testing in one day with high sensitivity, then you could take our process down to two weeks.

So we've talked about the vaccine. We've talked about the machine that made the vaccine. I'd love to take a second to talk about the company that built the machine. So from the moment that you started this company, you took a very different approach. And you've described it as having an engineer's mindset. Can you talk a little bit about what you did and how you thought about the early company build?

I had never built a company in hypergrowth. You know, I worked at Eli Lilly, I run Biomario, which is a big diagnostic company. But I had never built myself a company building very, very quickly. We decided to do something very atypical, because most biotech company are a one drug company at a time. What was very clear to us because MRNA is an information molecule is he made no scientific sense that this will be a one drug company. It would be either zero because we have a zero. because we run out of money before we can safely get to drug approved

or it would be a company with thousands and thousands and dozens and dozens of drugs because of a platform. And so once we realized that in the first hours of talking about Moderna, we started to become very worried and paranoid about geez, we don't know what we don't know about this technology because it's new. It has never been approved.

And geez, if we pick one drug, if we are wrong, and it doesn't work in the clinic, everybody will believe what people have believed for 50 plus years, which is MNA will never be a drug. And we most probably are going to go bankrupt. But if MNN could have worked, we will have failed society.

Because if we find a way to make this work, this will be dozens and dozens of drugs that are undoable using existing technology, like the VEF in the heart, and we will shortchange society, shortchange patient. And that was just unbearable. And so we spent a lot of time thinking about, okay, what are all the things that could make us fail?

We ended up zooming on four risks that we say if we can manage and reduce those risks, we will have a best chance to be the best version of Moderna. Those risks, we've talked about very publicly, especially when we went public. It's technology risk around the MRA technology. So, of course, if you do a new technology, you don't know what you don't know. There's going to be a lot of risk there are things not working, as you expect. Two, the biology risk. could have incredible risk

that your scientific hypothesis on the biology is incorrect and the drug will fail not because the technology wasn't working but because the scientific hypothesis on the barrage is incorrect. Then there was going to be a lot of execution risk

and then, of course, financing risk because we said like asset managers build a portfolio, we said picking one drug is crazy. It's like buying only one stock. And so we say let's build a portfolio of drugs and after many, many months of discussion,

we designed basically a pipeline of 20 drugs that we said we're going to take all those drugs in parallel to the clinic. So there will not be a binary event that the company makes it or not on one drug. So we diversify technology risk around six different technology applications from vaccine to drug in the heart

to a drug in the liver for genetic disease. And then for every application, we took several drugs to diversify the biology risk. And we launched that crazy experiment with, you know, 17 drugs in the clinic so far, which was going to create incredible execution risk, because it's harder to do 17 at the same time than one, and incredible financing risk because you need a lot of capital. But we traded those risks with eyes wide open because the other risk could kill us

with much higher probability, the technology and the biology risk. It's very difficult in this industry to take that balance on platform versus programs. And what tends to be the case very quickly is most companies, when they have to choose where to put an incremental dollar or an incremental head, they put it on the programs because those are the golden eggs and they want to move those forward to create value inflection. And as a result, the platform ends up getting starved. Yes. You started the other way around. You actually fed the platform and you fed the goose and then let the goose lay its eggs. Yeah, exactly.

The goose is more valuable than any egg. if you really believe you have a goose that's going to be making thousands and thousands and thousands of eggs you don't want to kill the goose on the first or second egg. Although most geese are not that fertile in biotech. Your is correct. And that's why I told the board that I was not interested to go public early because the capital market were going to force me to not invest in the goose.

Right. Because biotech fans like to bet on eggs, not on goose because there's not been a lot of geese before in this industry. So I'm not used to it. I mean, the record will show that you did a lot of things right. As you've built the company over the last 10 years, can you talk a little bit about the things you did wrong? That if you could get him back, you would do it over. But it's just one given the COVID situation is it took us three years to start working on vaccines.

So think about how the world will be different and more than I would be different. If we started working on vaccine from day one, we might have been able to go even faster for COVID. So that's the thing I regret and that's only. I made quite a lot of mistakes hiring people because I underestimated how intense our company is because I leave it every day. I thought initially that it was obvious that this is a small company

fighting for its life so people are going to work hard. It's brand new cutting edge giant so it's going to be complicated because every other thing is not going to work. So being able to manage uncertainty, people having a lot of grit, collaboration because making a drug is a team sport. A drug is a system of so many capabilities, a biologist, the talks people, the chemist,

the engineers to make the drug. And a lot of times people are coming from big pharma, I used to work in silos. And people who come from academia don't know how to develop drugs. It's a system. And like in a system, you get the best outcome if you really optimize the system working together. So the last question I would ask you, what advice would you give to the engineer that wants to get into biotech? So first you need to learn a bit about biology.

I mean, I have a chance that I spent my entire career in biology. So I've learned a lot on the go. I've learned a lot by reading. I'm a curious guy, so I read a lot. You can get biology books and learn. And I think he's understanding enough of biology so that you can be part of a conversation so that you can have an impact on decisions

and scientific choices that happen. And then you can go from there. That's wonderful. Thank you so much for joining us on BioEats World. Stefan, we're so grateful for your time. Thanks so much for joining us on BioEats World. If you'd like to hear more about all the ways biology is technology, please go subscribe to the A16Z bio newsletter at A16Z.com slash newsletter. And of course, subscribe to BioEats World anywhere you listen to podcasts.