The CEO of Moderna on the moment he first realized the company could make a COVID-19 vaccine
The following is a transcript from the a16z podcast, created by Silicon Valley VC firm Andreessen Horowitz.
In this episode, a16z's Jorge Conde and Hanne Winarsky spoke with Stéphane Bancel, CEO of Moderna.
Bancel shares how his company used the mRNA platform to develop and create the COVID-19 vaccine.
Listen to the podcast below:
The below interview transcript has been edited for clarity.
Lauren Richardson: Hi, I'm Lauren -
Hanne Winarsky: - and I'm Hanne, and this is Bio Eats World, our show where we talk about all the ways biology is technology.
Richardson: This week, in place of Journal Club, we have a very special episode featuring Stéphane Bancel, CEO of Moderna, in conversation with you, Hanne, and a16z General Partner Jorge Conde. And we're talking about the COVID-19 vaccine, right?
Winarsky: 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, Stéphane tells the story of not just how the vaccine got made, but everything about the machine behind this vaccine: the fundamentally new platform and mRNA technology behind the vaccine's development.
Richardson: 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.
Winarsky: Bancel describes what it took to go from pathogen to design to clinical grade product; how mRNA works (in a chocolate mousse 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.
Jorge Conde: Stéphane, could you have imagined a year ago that mRNA as a concept would be a household name?
Stéphane Bancel: No, and we had a lot of things going on in vaccines, in cancer, in autoimmune disease, in cardiology, in rare genetic disease, but I had no idea that 2020 was going to look that way.
Conde: So, if we flashback to January of 2020, can you talk a little bit about the process that you went through to realize that you potentially had a technology that could be a solution for this emerging pandemic?
Bancel: 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 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 symptoms - that's all it says.
And so, I sent an email to somebody working for Tony Fauci, Barney Graham, who we've been collaborating with for 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 or is it a virus?" And he 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 a day or two after, Barney sent me an email and said, "We learned from our contacts in China, it's not flu, it's not RSV, 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 MERS, 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. Barney's team did the same thing. And when they shared notes after around 48 hours, they'd designed exactly the same vaccine.
Conde: A couple 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 from what 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?
Bancel: So, right, Jorge, and this is a piece that I think most people in pharma don't appreciate yet about the power of mRNA technology: In 48 hours, we designed and locked down the entire chemical structure of a vaccine.
Hanne Winarsky: Unbelievable.
Bancel: We thought it up in silico, we never had access to a physical virus. And we designed the vaccine and we got the two teams at NIH and Moderna because we were so worried about making a mistake in the vaccine design, as you can imagine. So we were super happy when the team literally compared notes after two days with exactly the same design for our vaccine. Because it was an outbreak and we knew every day mattered, at the same time, we started to make clinical grade product to go into a Phase 1.
And what's really remarkable is that the vaccine that was reviewed by the FDA on December 17, it's exactly the same vaccine that our guys designed in January in silico. We never changed one atom, it's exactly the same molecule.
Winarsky: So, it's the same vaccine that took 48 hours to design?
Bancel: That's going to help hundreds of millions of people next year, yeah.
Winarsky: 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?
Bancel: 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 cell. So, the way I would 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 stored. 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 is it makes a copy of instruction only of insulin in the book - like my example of chocolate mousse - a Xerox copy, and texts it into the kitchen, in the cell, to make little machine called the ribosome that I described to my kids as little 3D printer, that reads the message 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.
Winarsky: But using mRNA as a tool in the way you've been doing it, that wasn't always an obvious approach. So, can you talk a little bit about where that began, that idea, and what it first looked like?
Bancel: Yeah, so it's actually very interesting. When mRNA and DNA were discovered, actually, people in a lot of universities tried to make medicines out of mRNA because it was a very logical use of mRNA. Just copy nature, make a synthetic mRNA, inject it into animals before humans, and it should 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 injected the mRNA in animals, animals would have flu-like symptoms of fever, vomiting, diarrhea (because mRNA, if we remember, most viruses in life, including COVID-19, is made of mRNA).
And so, for evolution, mammals have developed mechanisms to recognize foreign mRNA and, of course, when you inject the mRNA as an idea for a drug, that would be a foreign mRNA. And so, actually, people abandoned and just quit trying to make mRNA as a drug.
What happened in the 2010-2011 timeframe here in Boston is you had a set of academic at Harvard and MIT who started to play with mRNA again because there had 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 mRNA, you can make an mRNA that's immunosilent.
Conde: In some ways when you think about it, Moderna doesn't make therapies, right? You make constructions that the cell uses to make its own therapies.
Bancel: Yeah, correct. We don't give you a vaccine, we give you instruction for the cells 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 their immune system can make a neutralizing antibody and mature it.
So that if later if they get infected by the real virus, their immune system is ready to prevent the virus from replicating in their body and getting them sick. What gets people sick in infectious diseases is you have too many copies of a virus.
Conde: 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, you know, genome, and you said, "Okay, if I take certain pieces of code from this virus, and encode them in mRNA and deliver them to human cells, I am basically giving 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?
Bancel: That's 100% correct, Jorge. And the reason that mRNA, in my opinion, is so powerful is that you totally mimic in a human cell the natural biology of an infection, without giving it the virus. 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 3 that we are correct) that one protein of a virus - a very important one, the spike protein - if you're able to get a high quality of or a high quantity of neutralizing antibodies, you should be protecting people if they become infected with the real virus.
Winarsky: Why is it better to have the cell mimic this natural process than in the old technology?
Bancel: When you think about it, when you get an infection by an mRNA virus in your body, what happens? The virus of mRNA gets in your cell, uses your own cell machinery to make the proteins to basically self-replicate inside yourself, and then it escapes your cell, and this is what your immune system sees. So, if you think about it, the old technology of vaccines where you make an E. coli cell or CHO cell protein that then you inject in a human and that just circulates in your blood, that's not mimicking natural biology.
In our case, the spike protein, we designed the vaccine so it's made inside the cell - so in the human cell, not in the E. coli cell - and then we designed it to be transmembrane, meaning to stay attached to the cell and to be presented to the immune system that basically patrols, you know, in your blood in your body and will see that things sticking out of a cell that is not self. If you think about the 3D configuration of a B cell coming on to that protein, it's exactly like if it were a natural infection. Which is why if you look at the data across the nine vaccines we put in the clinic, the antibody level is so high. Because it's perfectly mimicking nature.
Winarsky: How did you know which protein and that one was enough? How did that process work?
Bancel: That's a very good question, and as Mr. Pasteur would say, and of course, he has a big role in vaccinology, "Only the prepared mind."
One of the things we were doing with Dr. Fauci's team for the last couple of years was collaborating on studying viruses that could become outbreaks. None of us thought we would see in our lifetime a global pandemic. The last one we were all aware of, as students of infectious diseases, is of course the Spanish flu.
And so, one of the things we got lucky with was that we'd been working for a few years together with Dr. Fauci's team as part of that project for outbreak readiness on the MERS vaccine, the Middle East Respiratory Syndrome, which if I'd used those words a year ago, nobody would have known what I was talking about, but now they already know it's another coronavirus.
We worked to provide to them mRNA for research grade, so animal testing, antigen design, and picking the protein that makes sense.
Because mRNA 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 designs they wanted to try in animals. They would vaccinate the animals, and then they would challenge them by giving them a high dose of a virus. The one that was the most protective was always the spike protein. They tried a lot of combinations, but spike by itself was always the best.
Conde: So, that 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.
Bancel: Correct. A full-length spike protein was always the best. Some companies went into the clinic with three, four, or five candidates and there were different hypotheses they were testing. We didn't have to do that, because we had tried it for a couple of years; we knew that with mRNA, our best guess was going at the full-length spike protein.
Conde: At a very high level, you are essentially printing these vaccines versus growing a version of virus or denatured virus. So, you can design it, you can print it, and then you can, you know, obviously, get this into people very quickly as a result. That's a remarkable part of this entire story that's probably somewhat under-appreciated, that allowed you and collectively us to move so quickly. When did you know, Stéphane, that, "All right, this is going to work," this is going to work for COVID?
Bancel: I had a very high belief that this should work from the beginning, so since January. This was the tenth vaccine we were working on, so I've seen the human data of the previous ones. And in infectious disease, unlike in oncology where the animal models tell you nothing, in infectious disease, if you look at a lot of data, there's extremely high translation from animals into humans. I saw the mouse data before we started, of course, dosing in humans. So, I knew the data in mice looks great, so because we had the nine vaccines before, I knew it was going to look great in humans, which we've learned, all of us, in May.
Conde: Can you describe, Stéphane, when you first saw the interim Phase 3 data and what your reaction was?
Bancel: So, it was a Sunday in November, I knew that the independent NIH-lead Safety and Data Monitoring Board were going to meet at 10 a.m. on Sunday. I told my wife and my kids, I'm going to be a wreck that whole morning.
I tried to pretend to work, but I was so distracted, I checked my email every two minutes, my phone every two minutes for text messages, and so on. Maybe a bit before 1 p.m., I got a text from my team saying, "Hey, get on WebEx, we're going to get the data."
There wasn't even a slide made, it was just somebody talking and literally reading to us 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 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 if you think about what this means when you connect those two datasets 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 with zero symptoms. And in the 5% case where you will get a disease, it will be mild disease, you will get no severe disease.
And when you think about what has happened to our society, the elderly, people with high comorbidity from hospitalization, when it gets bad, it leads to death, and the total impact on the economy, the loss of jobs in so many industries and some that will cascade. If you could have a vaccine where most people, 95% get no symptoms and the 5% that do get mild symptoms, never go and walk into a hospital, that will be a total game-changer. So, we listen to the data, and then I've talked to my team for a few minutes, you know, I don't think we were processing it. And then I left my home office and I called my wife, she was in the house, and I told her and she just started crying in the house.
Winarsky: I think that's what it felt like for all of us hearing it too, it felt like, you know, normal life could return and it was the promise of something like that.
Bancel: The human toll is gigantic, but then the piece that I don't think is talked about enough is the mental health toll happening to people at every age. All the young people, especially in more disfavored communities, are living in small apartments where mom is trying to work and kids trying to learn remotely without a computer or a good internet line - (we don't know) the impact this is going to have in terms of equality.
And then, of course, so many industries have been totally destroyed … I have not walked into a restaurant indoor since March and I won't go until I'm vaccinated.
Conde: 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've built over the course of 10 years that allowed you in January of 2020 to say like, "Hey, we need to develop a COVID vaccine."
I remember coming to visit Moderna in Kendall Square, that first facility you had. And what was interesting about it is 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.
Bancel: 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 all pharma and all biotech is in my book, 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 and pipettes and so on, you know, doing like what we all did in chemistry class and writing the synthetic route to get to a molecule that they want to do the biological effect that 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 everything 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 a clinical-grade product that you need to file to the FDA so that they give you a green light to go into testing this in humans.
It's a highly regulated, as it should be, process to protect people's safety. But in our case, it's always the same thing, because mRNA is always made of four same letters, the four letters of life like zeros and one in software, it's the same manufacturing process. This is like software or Legos, this is an engineering problem, it's an engineering technology, it's a platform.
The only difference between all Zika vaccines or all CMV vaccines and the COVID vaccine, it's only the order of a letter, the zeros and ones 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 by the Chinese to dosing a human. The first SARS, SARS-CoV-1 it took the NIH 20 months to go from sequence to starting the Phase 1 study. So, you went from 20 months to two months.
Conde: Which is remarkable. Are we in the plug and play future for vaccines?
Bancel: Oh, 100%. We're going after making a seasonal flu vaccine because as we all know, still 10,000 Americans die every year on average of seasonal flu. We believe we should be able to make a big bet on flu. And today we have six vaccines in development, we're going to have many more soon because for 10 years, you know, Jorge, we hoped that mRNA vaccines were going to work.
We believed scientifically they were going to work. But until you have a Phase 3 randomized, placebo-controlled study where you test, really, the prevention of the disease, you don't know. Now we know.
Winarsky: 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?
Bancel: It's when the mechanism of a disease is not well understood. So, we spoke about the 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 but still to this day, no approved vaccine against HIV.
Now, think about the awful world we'll be in right now if Dr. Fauci had to be standing on the presidential podium back in the spring and told everybody, "Folks, I'm sorry to tell you but this is awfully complex virus, we have no idea when we might have a vaccine." Think about the state of mind we'd all be in now.
The biology of rare genetic disease is very well understood. Why? Because kids got bad genetic information from their parents that they cannot make a correct protein and that's what caused their disease. They have a wrong instruction in their DNA, if you can get them an mRNA from our technology coming in their cells with the right instruction then they will have the right protein and they won't get sick.
If we think about cancer, on the other hand, or spectrum or Alzheimer's now, if the disease mechanism is not understood, we cannot drug it easily. We can try things, of course, we could make an mRNA behind that hypothesis and we could 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 is basically, all the labs 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 XYZ is the root cause of that disease, or those five proteins in this ratio are the root cause of that disease, then we can actually turn on the computer and we can now design a drug to go test that hypothesis in an animal.
Conde: 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.
Bancel: This is basically biology complexity or biology risk. The other dimension for us is the ability to deliver the mRNA in the right setting. We actually have become a delivery of nucleic acid company.
We realized that what would allow us to maximize the impact we could have on disease by helping as many people as we can over the next five, 10, 20 years, is the ability to bring mRNA to different cell types.
So, a good example today, 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 mRNA 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 lungs because they know the biology very well, and we work together to develop a delivery system to bring mRNA safely into your lungs and to bring enough mRNA 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 works, 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 are able to go so fast.
Conde: Yeah, 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.
Bancel: We're adding vertical after vertical after vertical, they bring mRNA into a new cell type. So, the vaccine is one vertical, getting mRNA into a tumor is another vertical. We have a very cool drug, where we inject mRNA in people's hearts after a heart attack, and here we got a protein called VEGF. For the biology geeks on the podcast, V-E-G-F, that is a protein that we all have the instruction in our DNA, which basically tells your body to make a new blood vessel. You use that protein every time you cut yourself.
Winarsky: Stéphane, 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?
Bancel: So, the robotics farm we have in our factory is basically just an 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 the 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 will 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 each other to make an mRNA molecule. Then the robot goes to the next step, which is you add the cap thing at, like, the nose of the molecule that you add again with another enzyme. Then what you do is you purify the mRNA, so basically, you pick the mRNA from all that water and enzyme, and nucleotides, nucleic acid, and so on.
And then when you have a pure mRNA molecule, after purification, you mix it with a lipid, i.e., fat, and that fat basically goes around and packaged like in a little bowl the mRNA. to protect the mRNA in your blood and to get the mRNA 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 3D 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 own medicine.
Conde: I remember from the earliest days, you were obsessed with the operations, you were obsessed with turnaround time, with throughput, with, you know, 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 cells' 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.
Bancel: That's what'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 happens in our cell is actually extremely logical.
We start from the sequence information of a virus, like in the case of our COVID vaccine, or we use the human genome, we put into a technology genetic base cassette, and then you click order on the computer, and you go again. And that's the vision I always had since day one,d and a lot of people at the beginning thought I was crazy because this industrialized, engineer-driven approach to drug discovery has never happened.
Winarsky: So, Stéphane, you've described this process, which is, you know, 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, you know, increases in technology that would speed this up even more?
Bancel: Yes, so it took us 42 days to go from sequence to shipping the human grade virus to Dr. Fauci's team. The big bottleneck is sterility testing, a very important quality control test that is done for any injectable pharmaceutical. To make sure that there is no bacteria in the product, the test takes two weeks because what you do is take a sample of your vaccine and you wait enough time.
Even if there's only one copy of a bacteria, by the time you have enough multiplication of bacteria, through a detection at 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 sterility testing in one day with high sensitivity, then you could take our process down to two weeks.
Conde: 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?
Bancel: I had never built a company in hypergrowth. You know, I worked at Eli Lilly, I ran bioMerieux, 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 companies are one drug company at a time. What was very clear to us, because mRNA is an information molecule, is it made no scientific sense that this will be a one drug company. It will be zero because we run out of money before we can safely get the drug approved or it would be a company with thousands and thousands and thousands of drugs because of our 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 mRNA will never be a drug and we most probably are going to go bankrupt."
But if mRNA could work, 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 VEGF in the heart. Then we will shortchange society and shortchange the patients, 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 the best chance to be the best version of Moderna." Those risks, we've talked about very publicly, especially when we went public. It's a technology risk around the mRNA technology, so, of course, if you do new technology, you don't know what you don't know and there's going to be a lot of risks, there are things not working as you expect.
Two, is the biology risk. You can have an 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 biology is incorrect. Then there was going to be a lot of execution risk and then, of course, financing risk because we said, "Like, you know, asset managers build the portfolio," we said, "picking one drug is crazy, it's like buying only one stock."
And so we said, "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 it will not be a binary event that the company makes it or not on one drug. So, we diversify the technology risk on six different technology applications-from vaccine, to drug in the heart, to a drug in the liver for rare 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 then created incredible execution risk because it's harder to do 17 at the same time than 1. And incredible financing risk because you need a lot of capital. But we traded those risks with our eyes wide open, because the other risk could kill us with much higher probability, the technology and the biology risk.
Conde: It's very difficult in this industry to take that bounce on platform versus programs. And, you know, what tends to be the case very quickly as 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.
Bancel: Yes.
Conde: You started the other way around. You actually fed the platform and you fed the goose and then you let the goose lay its eggs.
Bancel: 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.
Conde: Although most geese are not that fertile in biotech.
Bancel: Correct. And that's why I told the board that I was not interested to go public early because the capital market was going to force me to not invest in the goose. Because biotech funds like to bet on eggs, not on the goose because there have not been a lot of geese before in this industry so they're not used to it.
Conde: I mean, the record will show that you did a lot of things right. As you built the company over the last 10 years, can you talk a little bit about the things you did wrong and if you could get them back, you would do it over?
Bancel: The easiest one, given the COVID situation, is it took us three years to start working on vaccines. So, think about how the world would be different and Moderna would be different if we started working on vaccines from day one, we might have been able to go even faster for COVID. So, that's the thing I regret and that's on me. I made quite a lot of mistakes hiring people because I underestimated how intense our company is because I live 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 science, 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 great collaboration because making a drug, it's a team sport. A drug is a system of so many capabilities, the biologist, the toxic people, the chemist, the engineers to make the drug. And a lot of the time people coming from Big Pharma are used to working in silos and people who come from academia don't know how to develop drugs. It's a system and like any system, you get the best outcome if you really optimize the system working together.
Conde: So, the last question I would ask you what advice would you give to the engineer that wants to get into biotech?
Bancel: So, first, you need to learn a bit about biology. I mean, I have a chance to spend 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 later on. And I think it's understanding enough of biology so that you can be part of the conversation, so that you can, you know, have an impact on decisions and scientific choices that happen and then you can go from there.
Winarsky: That's wonderful. Thank you so much for joining us on "Bio Eats World," Stéphane, we're so grateful for your time.
This episode originally aired on the show Bio Eats World. The a16z Podcast covers tech trends, culture, news, company building, and innovation. The show reveals how "software is eating the world" and the future of how we work, live, eat, learn, and play. It features top industry and academic experts, company leaders and builders, book authors, and emerging voices and is produced by Andreessen Horowitz ("a16z"), a Silicon Valley-based venture capital firm that backs entrepreneurs in bio, consumer tech, crypto, enterprise software, fintech, and other industries.
Read the original article on Business Insider
