Why medicines are miracles of science and technology | AbCellera CEO Carl Hansen

Hi, I'm Carl Hansen. I'm CEO of Abela, here visiting UATX today. I have a chance to talk to the students about entrepreneurship and about the tremendous opportunities that exist in biotech, in taking foundational science and the breakthrough discoveries over the past few years and turning those ultimately into products that make a difference for patients in need. Thank you so much.

So, as mentioned, prior to being CEO of Abela, I was a professor for many years. One of the things you get to do as a professor is cram very early to give extemporaneous lectures, something I haven't done in a while. But this morning, when Eric texted me, I was busy trying to figure out what would be the arc of the talk today. And what I came up with is something that starts pretty high-level. So, my intent is to convince you that we are at a watershed moment in biology and that biotechnology is going to be not one of, but the most important sector in the coming decades. Two, I'm going to try to convey to you how bad we are at making drugs and how difficult it is. Three, how difficult it is to build a company that has the resources and the power and most of all, the longevity and the time scale that is needed to actually make a difference in the world. And then, explain to you why I think it's still a great place to build a business, and that the impact that can be had in this particular sector, in my view, is paralleled by very few others, if any. And lastly, I will then, you know, give you sort of a Cole's notes version of what we've been doing at Abela over the last 12 years, sort of the highs and the lows, where we are today, and where we're going to go. And my hope is that most of this talk, at least half of it, will be not speaking to you, but speaking with you about questions that you have about the sector, about entrepreneurship, leadership, and really just about anything else that's on your mind.

I do think that what is happening here in Austin is remarkable. In no, in a very real way, you are all entrepreneurs on what is a very worthy endeavor to revitalize one of the most important institutions not just in this country, but in the West broadly and beyond. And I was, you know, frankly honored to get a chance to meet the students here and have had a great day. And as I said to Raina early on, though it's small beginnings, you know, the oak starts with the acorn, and it looks like it's firmly planted here today.

So with that, one of the things I don't think we touched on is that I've got no business being a CEO of a biotech company because I have no formal training whatsoever in biology. I think I did, that's not true. I think I took one class in undergrad that was a bit of a survey course. Instead, my training was in physics. And so I thought I would start today with a metaphor from physics.

So in 1927, 1927, this was the heyday of physics. There was a meeting on quantum mechanics in Belgium, in a country, in a city called Solvay. And there's a picture of this meeting that you can find on the internet. It's often described as the most intelligent picture that was ever taken. And there are 29 attendees at this meeting. I think 17 of those people went on to win the Nobel Prize. So if you look across the ranks, you'll see in the crowd of people that are well-dressed and sitting there, Schrödinger, Heisenberg, Pauli, Compton, Planck, Niels Bohr, Albert Einstein, Marie Curie, de Broglie, Max Born. I'm forgetting many names that you would remember. I was an undergrad in physics, and so these, I never knew this when I was an undergrad in physics. And you, in every textbook, every law, every physical principle bore the name of one of these people. And you imagined that somehow this was the accumulated wisdom of centuries of work. But it wasn't. It happened at a single moment in time. And although these people were unquestionably some of the most intelligent scientists that have been produced, the hard fact is that if they had lived at another time, we would not know who they are because they came at a moment where there was an explosion of understanding and knowledge that rocked, completely rocked our comprehension of how the world works at a level so profound that it borders on the divine.

So that's what happened in physics since then. And lots of great things came out of that, by the way. And the impact, the translation was often delayed. So, you know, by the '40s, we had splitting the atom. The work on quantum mechanics laid the stage for solid-state physics. The transistor came out in the '60s or '50s. Today, we have an entire industry based on technology. It took about 100 years for less than 100 years, maybe 80 years for those early insights into fundamental science to percolate through the system and to profoundly change our lives. But in basic physics, where I trained, which was a wonderful place to train because you learned how to think logically, you learned rigor, you learned how to work hard, you got intuition about the way the world works, the opportunity for discovery is very, very thin today. We have gotten to the frontier of physics, and there are still very smart people that are pushing the envelope, but it is nothing like it was in the 1920s.

So that's a bit of a long intro, but I want to posit to you that if you held a Solvay conference in biotech, you would hold it today or sometime in the near future. That is the moment that we're at today. So when they had the Solvay conference in physics, they weren't the first people to do physics. It went all the way back to the ancient Greeks, and we had Copernicus and we had Newton, you know, maybe 150 years before that, but the foundation had been laid, and it exploded in biology. If we had, you know, a Copernicus and a Newton, they might be Mendel and Darwin. Mendel and Darwin lived at the same time, and they both passed away within a couple of years in the late part of the 19th century. If you think about our modern understanding of biology, it probably starts with the discovery of the double helix, the code of life, and the structure and understanding of how we encode information in that molecule. That was discovered by James Watson and Crick in 1968, the year before we went to the moon. I think the world probably didn't really notice because they were looking at other things that were happening. James Watson is still alive today, right? So there is a person alive today, I think he's in his 90s, who was at the very, very beginning of that.

In modern molecular biology, a lot of it relies on the ability to sequence and manipulate and change DNA. And the core technology that allows that is called PCR, Polymerase Chain Reaction. PCR's Chain Reaction was invented by Kary Mullis while he was driving with his girlfriend, apparently, and they had a fight. That's part of the story, in 1983. So Steve Jobs was about to release the Apple, and we had just finally had the ability to isolate a known sequence of DNA and start to think about manipulating it. Kary Mullis ended up getting the Nobel Prize for that, and he got it alongside of Michael Smith. And Michael Smith was a UBC professor, where I was a professor for many years. And as an undergrad, I got to have dinner with Michael Smith. Sadly, he's passed away, but he made a contribution in site-directed mutagenesis, which was the first example of using that Polymerase Chain Reaction technology to make specific mutations to engineer biology, in 1983.

I trained in physics, and when I got to the end of my physics degree, I realized that I was really, really good at it. Maybe second in my class, and I was at least an order of magnitude worse than the first, than the first guy in my class. And I recognized that, you know, while I had gained a lot from the training, I probably wasn't going to be able to do something that really moved the needle in physics. And I had some intuition that biology was really taking off. So I moved from my physics training and I tried to get into biology by joining the lab at Caltech that was run by Steve Quake at the time and started to train in bioengineering. The second, the first year I was there was 2001. And in 2001, we got the first draft of the human genome. How many people in this room were born in 2001? Not that many. But for me, this seems so, perhaps for you, this seems like a long time ago. This is one of the things about the human lifespan is that we, we tend to not be able to recognize the changes that are happening right around us. But I remember that, and it was a watershed moment. And we had only about 90% coverage of the human genome, and it took, you know, thousands of scientists across labs around the world, and it cost roughly $3 billion to draft it. And that was, that was a huge moment. The idea was that that was going to bring a deep understanding of all these genes, and drug development was going to take off.

Since that time, the cost of sequencing a genome has gone down about 3 million-fold, and the time to do it has gone down about 3,000-fold. So today, there have been millions of genomes sequenced. They can be done for less than $1,000 a piece, and a technician with quite an expensive instrument can do it over the weekend in a lab. If you look at the rate of change of that ability to read DNA, it outpaces Moore's Law by orders of magnitude over that period. I would be hard-pressed to come up with any domain where we have seen progress and an explosion of the technological capabilities that underlie something fundamental in a field more than that in just recent times.

And this is some of these hit the popular press, and some of them don't. You know, we've had the invention of induced pluripotent stem cells. A guy named Yamanaka understood or realized that you could insert genes into cells and turn them back from late differentiated cells back into stem cells. It's a core technology to be able to clone and to manipulate mammalian life. More recently, Jennifer Doudna discovered CRISPR. CRISPR technology lets you specifically edit mammalian genomes in a way that was completely impossible only 5 years ago. Just last year, David Baker got the Nobel Prize along with colleagues at Google or DeepMind for his work on computational protein engineering. And the list goes on and on and on. I can make a list of 20 people that have made foundational changes, and those people, many of them are not much older than me, and most of them are alive. So if you had the Solvay conference in biology, the only problem would be that you'd have some empty seats, and you'd have to wait a few years for those people to show up.

Okay, so just to drive home how recent and how spectacularly fast this is, I want to borrow from a metaphor that John F. Kennedy used in his speech when he talked about going to the moon. And the metaphor was that if you took all of known human history, 50,000 years, and you crushed it into a 50-year time span, which is how old I am, so take all of human history and crush it into my life, then the discovery of the double helix happened this morning, and the other things that I relate to you happened after lunch, and some of them happened just before this talk. Right? So in the span of human history, we are at the inflection moment where there has been zero progress for thousands of years, literally. And in this, in the span of less than a century, we have completely opened this up. So that's, you know, if you're thinking about what you might want to study and where you think you could make a discovery, that's a hell of a place to be.

And of course, it's important, right? Because we're all made of molecules. We are biological entities. We don't always work perfectly. We have disease. And it seems that there's an opportunity to use that information to create products that can relieve suffering and extend life and improve health. That's what biotech is all about. So you would think that we are in, you know, the absolute heyday of biotech. And in some ways, we are. There's been tremendous progress, and I don't want to diminish that. But if you're in my industry, that's not the narrative that you hear all the time. The narrative you hear is that drug discovery takes too long, drug discovery work fails too often, it costs too much money, the productivity of the industry is going down and down and down. Eric and I were on a fireside chat, and he pulled a number, and roughly, right, it depends who you ask, but the all-in number, including failure and cost of capital, is somewhere on the order of $2.5 billion per drug. Now, most of those drugs will actually never make that much money. So that's not a great industry to be in.

If you look at the number of new therapeutics that are created every year, it's in the dozens, despite the fact that there are thousands of companies, and large pharmaceutical companies on their own, I think they spend over $300 billion a year on R&D. So the output is not that great. And it's worse than that, because if you count all those drugs and you asked how many of those are actually going after a big indication, and how many of them are real innovation, not following something we knew worked, which is important and it creates new options and competition, but something that's actually addressing a disease that was not addressed before, the answer in any given year is less than a handful, and many years it is none at all. So it's been, it's been really, really hard. And I just thought I would emphasize why that is.

So in most businesses, let's say you're, I don't know, let's say you're selling cars, making electric cars, that seems appropriate, given where we're at. You know, it's an engineering problem, and you can prototype it, and you put the thing together, and you have marketing. And as soon as you have that actual model and you've run it through a few tests, you can sell it. There's a concept of a minimal viable product, there's a concept of testing the market, of iterating, of new designs. Okay, that's not how biotech works. In biotech, the first problem is I need to come up with an insight that makes me believe that if I make a certain molecule, it's actually going to have an impact on human health. And the reality is, because all those technologies are so new, and because our understanding is so bad, we typically haven't the faintest idea what is actually causing disease. That's putting it perhaps too strongly, but if, you know, if at some time in the distant future, we have 100% certainty that our drug targets are going to work, we are now at something like 2% of that. So we just fundamentally don't understand how this works.

So first, you have to come up with that idea. Then you have to solve the problem of creating the molecule that will run you, you know, maybe anywhere from $5 to $10 million. It requires a conspicuous confluence of expertise from various disciplines. Then you have to manufacture it at a level, a regulatory standard that is rightly high, because it's going to go into people. And after you, that entire gauntlet, and meanwhile, your company is burning money the whole time, now you get to start not selling it, you get to start testing it. And testing it means first going into safety trials in Phase 1. And if it works in Phase 1, then you set up a new trial in Phase 2 to show if it has efficacy. And then you have to run two Phase 3 trials. And you do that to prove that your drug is safe, and that your drug is effective. And that process generally takes hundreds of millions of dollars and anywhere from seven, in the best-case scenario, to 12 years of development. And by and large, for many indications, you don't know if the product that you made is any good until you get that Phase 2 read or maybe the Phase 3 read. So the feedback loop is horrendous.

So developing drugs, I would posit, is the single hardest, most technologically deep, scientifically risky, capital-intensive, time-intensive product that gets made in any industry, full stop. There's a terrific founder named Josh Boger who was one of the early CEOs at Vertex. And I saw him give a talk, and he put it nicely, so I'll steal his line here. He said, if, if you want to go to Mars, which also seems appropriate here, if you want to go to Mars and you give me a hundred million dollar, hundred billion dollar, pardon me, $100 million, probably can't make of it, $100 billion, I'll put you on Mars because that is, it doesn't break the laws of physics. This is an engineering problem. It is hard, it's complicated, there's logistics, you have to get it right, the margin of error is small, but it's an engineering problem. If you give me $100 billion and say, Carl, go cure Alzheimer's, I will say to you, I'll give it my best shot, but I don't have no idea if it's going to work, and I probably wouldn't give it odds better than 10%. And that's the industry that we work in.

So this is a really, really hard place to build a career and build a business. And most biotech companies, the vast, vast majority, I don't know the number, but I wouldn't be surprised if it's more than 90, 96% or 7%, never work on a product that ever gets to patients. Right? So when you sign up for biotech, you know, you're signing up statistically for failure. And the vast majority of researchers in the industry never work on anything that ever becomes a product for patients. It's pretty bleak. The only thing more bleak than developing a drug is trying to build a company that can scale and reproducibly build and sell drugs. And if you think about it, the reason is actually pretty obvious because you're starting from scratch, and you need to do a lot of things. You need a great idea, you need to assemble a huge amount of talent, you need very expensive capital infrastructure. Then you get a shot or two before your investors run out of patience to get something to the clinic that shows a hint that is enough to convince people that you're going to be able to move forward. And if you miss that, you're done. But if you hit it, then you go to Phase 3 and you raise more money. And ultimately, if you have not built up the capabilities and the engines to follow up that next molecule, then when you finally get it to the market, you're worth much more to a large integrated company than you're worth to yourself, and you will be bought.

And as a result, the number of companies that start from scratch in biotech and are able to actually scale, I think is probably one of the worst in any sector. And I did a little, a little sort of thinking to put some numbers and quantify this, and I'll share it with you. So the phenotype of a company that could reproducibly make drugs and has a potential to scale up and be like the next Regeneron or Pfizer or Lilly, okay? One, it needs to get a hit, needs to have a drug that is a blockbuster or close to a blockbuster that wins and that it owns. Two, it needs to have the capabilities internally to reproducibly generate those. The capability building is an immensely difficult thing on its own. And three, it has to have a whole series of drugs lined up behind that first one that convince people that it's worth more than just that single asset. Okay? So that's the phenotype.

So we took that phenotype and we looked across all public companies and we said, roughly how big is a public company that has that phenotype? And we could quibble about what that number is, but we landed on from a market cap of about $20 billion. Okay? So a $20 billion biotech company typically, it's a bit of a rough cut, but typically has a lead product that's a winner or going to be a winner, it has a good pipeline behind it, and it has some capability, whether it's expertise in biology or a platform technology or some infrastructure advantage to reproducibly develop drugs. So you take that metric and look out in the world and say, how many companies are there like that in the world, full stop? And the number of companies, I think last time I checked, is roughly 35. So there's 35 companies in the world that actually make drugs in a scalable way that have a market cap above $20 billion. So that already is not very many. If you consider that in 2020 alone, there were nearly 100 companies that went IPO. So literally thousands of people attempting to do this, and over all of history, this many companies are left standing.

But when you look at these companies and now you say, when were they founded? And what you'll see is at the top of the list are companies that were founded in the 1800s, like these are legacy companies, the Eli Lillys, the Mercks, the J&Js. These are companies with a very, very long history. So you start to bring the event horizon back, or the timeline back, and you ask, how many companies have a market cap over $20 billion and fit this criteria and were founded within the last 40 years? And today, it was higher before I checked this morning. Today, I believe that there are six. Six companies. So between 40 years and 30 years, the three are Regeneron and Vertex and Gilead, all sort of hovering around hundred billion dollar companies. Between 30 years and 20 years, there is Alnylam, that's the only one. And below 20 years, there are two, and it's BioNTech and Arvinas. BioNTech has a huge amount of cash on their balance sheet because they were one of the big winners in COVID-19. So if you took that out, and I think they may well survive, but if you took that out, really, you've got, you know, five companies in the last 40 years that have managed to get to that critical, critical size.

And so, you know, as someone who has an ambition that we've had for many years to build a company, you look at that and say, wow, from an actuary, it's impossible. Like the odds are stacked against you so badly. Until you realize that the number, the number should not be corrected by the number of companies that are started, rather it should be corrected by the number of companies that were started with any true intent of building a company that would actually be able to scale. Because that's not what happens in our industry. The investment horizon is typically, you know, Eric said it today, typically between seven and 10 years, and you cannot get anything to the market in seven and 10 years. So if you're running a biotech company and you've got a business plan that goes seven years, the top line, the revenue is zero, it's going to be zero, you have a loss-making enterprise. And so people set up their companies not to ever get that hit and follow it up, they set it up to show dispositive data that gets someone else convinced so they can hand it off to someone else and have an exit. And baked right into the business model from the very beginning is the idea that we will never scale this company and we will never go to the market.

And I think it doesn't necessarily need to be that way, but finding ways around that requires that you solve a very tricky problem in keeping teams engaged and capital engaged for a long enough time you have a hope of making that work. And you, and I'm happy to talk about, you know, some ideas of how to do that, but I won't at all pretend that it's been solved because it requires, it requires a, it requires some careful planning and a lot of good bounces along the way to make that happen.

Okay, so I told you the science is unbelievable. This is a watershed moment, maybe the most important sector for scientific discovery and exploitation in the coming decades. But developing drugs is almost impossibly hard, and starting a company is the only thing perhaps harder than developing a drug. So why, why would anyone go into this? And someone made a, someone asked a question today, and the question was, you know, about academia and stuff, and that, you know, academics didn't do it because they were, it was posited that academics don't do it because they're not sort of wired to make money. And my repost to that was, you know, anyone who looks rationally at biotech is not doing it because they want to make money. Are you kidding me? You've got to run the numbers. I think the reason is, and you know, a lot of people are cynical about this, the reason is that the impact that you can have when you get this right is unbelievable.

And, you know, despite the fact that the industry often gets caricatured as, you know, greedy capitalists, and there have certainly been bad actors, if you spend time at the JP Morgan conference and you go and you meet executives at these big companies and small companies, and the people that work in these companies, they are not there because they think it's the easiest way to make money. They are there because they want to do something that gives them real purpose in their life and to feel like they're not wasting their days. And in the end, what that means is delivering products that actually make a difference to patients. So I, I just wanted to maybe make that a bit more real for people.

Okay, so I would say that when this works, this is nothing short of a miracle in science and technology. Okay? Who knows what the drug Keytruda is? Who sort of, Keytruda? Okay, so Keytruda, I believe today is still the highest-selling drug. It was developed by Merck. There's another very similar molecule that almost at the same time, in fact, that had a head start, was developed by Bristol Myers Squibb. Keytruda works by engaging on lymphocytes, T-cells, to take the brakes off of T-cells to help them to attack cancer. So instead, it's a cancer drug that doesn't work by directly killing the cancer, it works by boosting up the muscles of the immune system to go and fight the cancer itself. It doesn't work for everyone, but when it works, it is a miracle.

So someone can come in who has, let's say, a metastatic melanoma, and you take a CAT scan of that person, and what you'll see is an outline of a person with black dots everywhere. And this person knows when they look at that CAT scan that nothing is done. They will have mere months to live. Prior to Keytruda, that was the reality of that situation. Now, for some, some number of patients, a minority, but a significant minority, let's say it's 30% or 40%, this drug can be given to the patient, they can come back a month later, and they can take that CAT scan, and there is no tumor, and they felt pretty good the whole time as well. Like think about that. That is like the hand of God came down and pulled the cancer out of someone. That's not too strong a word if you're the person that is suffering from that. That is the impact that can happen.

Another example, who knows what Luxturna is? Luxturna. So Luxturna is a drug that was developed to treat a much smaller group of patients, but, you know, children that are born with a genetic defect that makes them blind. And using viruses, you can inject a gene back into the retina, and it will express. And these kids, after a few weeks of recovering from that surgery, can see. And they walk around. And if you watch these videos, and you see a video of a child before this happens, trying to navigate a maze, and they're moving along, and they're kind of feeling with their feet, and they cannot see at all. And two weeks later, they walk right through the maze. Like the blind can see. That is a miracle. It's a miracle of science and technology. And there are many others.

You know, one of the companies I truly admire, Regeneron, developed a series of drugs. You know, one of those drugs called Dupixent, one of the biggest drugs in the world, is treating something that is not fatal, but something that absolutely torments people, and that is atopic dermatitis. So we think about atopic dermatitis as a rash, but you know, some kids that get this are covered with these plaques, and they are horrendously itchy, and they cannot concentrate, and they cannot sleep. And for the patients where it works, not everyone, but it's a fantastic drug. You take this, and they're gone, and you get relief. And if you have a kid, if you have a kid that has suffered from that, that is a miracle. It is an absolute miracle.

So that's what this industry is actually about. And I, I maybe wanted to just take a little bit of a detour into public perception and policy because it wasn't that long ago that the villains in the corporate world were the companies that sold tobacco. I think probably rightly so, right? You know, advertisement was used to create a culture of smoking. You know, I think I'd probably enjoy smoking, but it turns out it's really bad for you, and it was literally causing cancer, and there was rightly public outrage against the companies that were causing cancer. You know, fast forward now 30 years, there is public outrage against the companies that are curing cancer. It's actually happening. Like something has gone very, very much awry here. And I think a lot of that is because people don't understand what I just told you: how hard this is to build a drug, how much money it takes, how difficult it is to get someone to build a company that can do this, and what is the true motivation of the people in this industry that do it.

So if we want more miracles of science, and I think we do, and I know that everyone in this room, sadly, is going to run into a situation in their life where they would want another miracle of science, we have to find a way as a society to value it and to pay for it. So one of the myths is that drugs are too expensive, and that the country, whether it's Canada or the US, can't afford it. Okay? So I just wanted to bust that myth. First of all, if you do a proper accounting, the return on investment for biotech and drug development is negative. It's negative. So we have an industry that makes a negative return, it spends more money every year than it makes. So just on first principles, drugs are not too expensive, they're not expensive enough. The flip side of that is that we need to get better at making them and be more productive. But the truth is, if we pay less for drugs, we'll have less and less innovation and less and less drugs.

The other part of it is that, you know, people act as though we can't afford this as a healthcare system, not recognizing that good drugs, drugs that really work, are the most productive, most effective tool that we have for helping human health. The quip is that, you know, a doctor without drugs and medical devices is just a priest. It's true, right? If there's nothing you can do, it's about, it's not about much, actually. Right? So it is the tools that we use to treat disease. And the last piece that I wanted to maybe bust was that, you know, in the healthcare system, so in the US, for instance, I believe total healthcare spending, which is a problem and growing very quickly, is roughly $4 trillion. That's a big number, right? The amount of that that is branded, patented drugs is less than 10%. And that number has stayed roughly the same for about a decade, despite the fact that more and more drugs have been made that are better and better and for more and more indications. Right? So if you were a Chief Financial Officer of the company and you said, hey, we're running this line of business and we're going to quickly run out of money, we need to cut back, and then the response was, well, let's look at 10% of the budget that's most productive and cut that back. You'd ask, hey, why aren't we looking at the rest of the delivery system here? And that, that honestly is where most of the fat is.

So I think it is incumbent upon us in the industry, mostly, to help get these stories across to people and have them understand what this is really about. This is an industry that we need. It is an industry that will save money in the long term. And it is an industry where you don't have to make a slide deck that spins up some artificial reason for why this is going to have impact. You see this in a lot of companies, like, you know, our company is going to connect dogs with dog food and make your pet happy. Or like, no one says that in biotech. It's obvious, right? Got people that are sick, they need medicine. Got people that are dying, they need medicine. So as a society, we should be holding these companies up as the most important, celebrated companies in the industry. Companies like Eli Lilly are the pride and joy of the United States and frankly of the Western world, one of the most innovative, impactful, fantastic, well-run companies in the world.

Okay, so I promised I'd say a little bit about Abela. So I'll tell you my story really quickly. So Abela is a biotech company. We're focused on making antibody therapeutics. We started the company back in 2012 from my academic lab at UBC. And the core idea was that we were going to use microfluidics to be able to enable very rapid, scalable analysis of the properties of individual cells. And that the cells we're going to look at were the immune cells of the body because those cells are fundamentally different. They make different molecules called antibodies. And it turns out people actually care about antibodies because they are the largest and still, in an absolute terms, the fastest-growing class of therapeutics that exist.

So we had this idea, and we started as a completely ragtag group of academics. It was myself, it was some engineers, and some scientists in my lab. And the six of us had sort of this broad idea that, hey, it should be a valuable thing to be able to look more deeply through the immune system to find antibodies of value. As soon as you start a company, you know, the first thing you're told to do is to make a business plan. And I think, you know, there's probably very little value in showing anyone the business plan. There's a ton of value in the mental process of going through the plan and starting to bring some rigor onto it. Eisenhower has a great line like that: "Planning is useless, but no plans are useless, but planning is essential." There it is. There it is. Plans are nothing, planning is everything.

So we started to look at this. And then, you know, we were not drug developers, and we had no illusions that we were going to go out and do the classic model of swing for the fences and hit a home run on the first swing. So instead, we had the idea that, hey, we are technologists, know a lot about technology, a lot about interdisciplinary research. We will build tools and we will provide access to that technology to other people who are focused on making drugs. And in exchange for that, we're going to get paid a little bit of revenue upfront, and we're going to keep a little piece of the drug if ever it is successful, so typically as a royalty. And this was not a completely novel idea. This is an idea that was really pioneered by a company called Adimab, that was the brainchild of Eric, who's in the audience today, who successfully had built a company like that, you know, roughly seven or eight years before.

So we went out and started to work on this. And in 2014, I decided, well, we better raise some money. And so I went all over the all over town in Vancouver. And remember that we're located in Canada. You know, none of us had been connected to anyone in venture. We didn't know anyone who started companies. And the ecosystem in Vancouver was such that no one even knew what an antibody was. And so the punchline is that despite trying as best as I could and having real conviction that this was going to be a thing, I failed miserably at raising any money, literally zero. So we had to pull back. And so instead, what we did is we called up our friends and family and said, hey, you know, take a flyer on us, we think this will work. And we ended up raising just under a million dollars Canadian in 2014. In hindsight, the failure to raise money on that first round saved the company from doom for sure, because if we had raised money, we would have been on the clock, and we would have run out of time to get to any reasonable value before it was time to exit the company. So that was not insight, that was necessity, and necessity that turned out pretty well.

So instead, we had, you know, only a million dollars Canadian. We stayed at the university, started to get some clients, started to bring in some revenue. And by 2018, we had scaled up to roughly 50 people. We still hadn't raised any additional money. We needed to get out of the university and went down to San Francisco and met, you know, the first venture capitalist that really believed in us, John Hurl at DCVC Bio. And John did our Series A. It was $7.5 million US. So anyone who follows biotech knows that today, the headlines are a $100 million Series A. So $7.5 million was not a lot of money. So that was in 2018. And we were starting to scale this business and really good traction.

And then the thing that really, really I think set us up for success was in 2018, at the end of 2018, the Department of Defense had a program called the P3 program. And for those that don't know, DARPA, Defense Advanced Research Projects Agency, the agency that takes moonshot high-tech bets and tries to be way ahead of the curve, invented the internet, GPS, had put in, put together a program that is probably one of the most prescient and effective programs that was ever done by a government agency. They said, in 2018, we want to build a technology so that if a pandemic was suddenly to happen, you'd be able to take blood from a patient, search through the immune system, find an antibody that responded to the virus, manufacture it, and then deliver it back to the population as a therapy or as a prophylactic. Break, and do all of that in 60 days.

Now, I just told you that normally drug development takes 10 years. So if you said 60 days in 2018 to anyone in drug development, you quite literally got laughed out of the room. The eyes would roll back in their skulls, and you were gone. And that really is the criteria for DARPA. If you're not laughed out of the room, typically they don't think they should be in it. So we had been on a previous program and had been a subcontractor. And then in 2018, decided, okay, we're going to try ourselves, as this tiny little Canadian company, to become a primary contractor with DARPA. And the reason we got it is that I had spent 15 years doing nothing but writing grants in academia. And this was the most impossible Super Bowl of grant writing that you could ever see. It was hundreds of pages, you had to cobble together huge teams, massive budgets, you had to address unreasonable expectations. We got this thing done, and we landed the grant.

So in 2018, we started working on this pandemic response. And luckily, a lot of the technology was right in line with our business. This was about rapid antibody discovery. We had done a couple of capability demonstrations, including one on a coronavirus. And we're coming up to our third when in early 2020, COVID-19 hit. And we got a call from DC saying, "Hey, now you're live." So until then, this had been an interesting theoretical project where I don't think anyone believed we were ever going to get the opportunity to use it. And here we are, only a year and a half into the program, and we're being called to step up and make a pandemic response to the pandemic.

So we got the first ever blood sample from the US. We were able to screen it. We were able to find antibodies that were effective against COVID-19. And then, because we had built relationships across the industry, was able to get in contact with folks at Eli Lilly, who were also interested in doing their part as an industry in responding to the pandemic. And so we partnered with Eli Lilly. And the upshot of that was that within 90 days of getting the blood sample, we had the first patient that was dosed with that drug. And that is currently, I think, by far a world record in the speed of drug development. Unless we have another pandemic, it's likely to remain a world record forever because a lot of things went together to make that happen.

We then, that drug worked. It then came off. We developed another one. And over that time, roughly 2 million people in the US were treated. It was used for moderate to severe patients, early on infection. And the clinical trial showed that the fatality rate in that population was somewhere between 4% and 5%. But if treated early, the fatality rate was zero. Not a single fatality in anyone treated with this therapy early on. So across, you know, 2 million patients, and the severity of the virus changed a little bit, I'd estimate that saved roughly 50,000 lives. That also was a huge boom for the company.

So just, I'll finish this up and then we'll get to the questions. So just before then, so I remind you, up to 2018, we had raised $7.5 million in venture and $1 million from friends and family. We were getting ready for a Series B where we brought together $110 million from some of the very top investors in the world, including Peter Thiel, who's got some connections to the institute, I believe, and some other top investors. That closed in March, just as the pandemic was happening. Right then, the world got excited about biotech. So in addition to 10 years of very cheap money, there was suddenly a strong interest from everyone in investing in biotech companies, and a lot of profile. And the stock market was going absolutely crazy. If you look at tracks of biotech companies in 2020 and 2021, I think there were 170 companies that went public. As...

As compared to maybe 20. So, in March, we had a plan. We're going to take this Series B and go public sometime this year, in 2025. Uh, but suddenly, you know, the markets were good, we had a product that was working, we had a royalty from Eli Lilly, and we were able to go public at the end of that year. So we raised $555 million on the public markets. At the time, it was, and still is, the largest biotech IPO in Canadian history. And I think at the time, it was the second or third largest biotech IPO, full stop, for any company. Uh, the company valuation went from something like $300 million post Series B to on the first day of trading, $7.17 billion.

It was mentioned that I suddenly became a billionaire. So, I, I, uh, I entered 2020, you know, with a liquid net worth of probably $100,000. And, uh, by the end of the IPO, it was supposed to be, or at least on paper, it was something like $4 billion. This was, this was completely, you know, this was disorienting. And, um, you know, Forbes did an article. Everyone got very excited. You feel like everything you're doing is absolutely on track. It's very hard to see the big picture, uh, from where you are right there.

The Lilly drug sold well. We brought in about a billion dollars in royalties from that drug. And the thing that really did is it allowed us to complete the project of building capabilities that we had started way back in 2012. So, since that height, inflation came up, interest rates came up, the biotech market has tanked completely. Um, you know, our stock went from $70 to, I think, as low as $2.50. It's now probably at about $3.50 or so. And in my mind, through that entire period, the company was getting stronger. The company was doing good science. We were executing exactly what we needed to do. And, uh, in hindsight, I think it's, it's one, it was a great one. One, it was great to bring the resources to actually cross that gap and get in a position to build a company that can scale. But also a great education in realizing that, uh, what other people are telling you is valuable is not what you should pay attention to.

And I'm going to get into a little bit of economics here, and I, I probably shouldn't because I don't have any training. But at some point, someone's going to tell you what an efficient market hypothesis is. And maybe that works. And I think there are some people that believe it. But it depends on a few assumptions. And one assumption is that all information is available, that people are rational, enumerate actors. And in biotech, both those things are not true. The lesson that I think we learned through that is, um, you know, you, you really need to look inward and ask yourself, what are the real examples, the pieces of data, the things that I can see and touch and feel that tell me that I'm on the right, right track? So that I have feedback. Because if you listen to others, not just on public markets, but in your life, if you listen to others, you will be blown off course. And so having conviction and staying the course is probably the big thing.

So, just to finish the story, um, about a year and a half ago, having completed the building of capabilities, I believe we now have the world's most enabled technology for creating antibody drugs. And having got through that build now with 600 people and, uh, sufficient capital to take multiple shots, uh, we've decided to turn this company from the model of doing work for others to doing work on our own behalf. And this year, we'll be taking our first two products into clinical trials, and have a plan to bring two more per year over the next five years or so. And so for us, you know, that, that recipe that I talked about, you know, get, find a winner, back it up, and have the ability to follow it up over time, is what we're after. And the thing that's missing right now is to find the winner. And that's where our focus is. Um, so I'll stop there. I probably went longer than I intended. Thanks.

All right, I have a couple questions. Um, I'll try to go through them quickly. Um, first of all, I didn't hear you mention anything about regulation, which is a huge question in the biotech industry during the whole talk. When you're thinking, first of all, you spoke 7 to 12 years of development as sort of like a necessity and completely unavoidable. Would you recommend any changes in regulation? Do you think anything is going to happen in this new administration?

That's a great question. I, you know, there's a, there's a, you know, libertarian tendency to blame everything on regulation. And I, I think that there certainly could be some improvements. By and large, I think the FDA does a really good job. So, you know, they're, you know, you, you have to remember that when you bring a drug forward, it's going to be given to a lot of people. And we need to make sure that these things are safe, and they are done to high quality, and that they do actually work. And some of these things just take time to test. Uh, so an example is like an Alzheimer's drug. If you're doing a drug to prevent the progression of Alzheimer's, that progression happens over a decade. So you need hundreds of patients taking this for a decade, and that ends up being an expensive proposition.

Now, in terms of your question, the things that I think could be done better, uh, there could be less, uh, there are ways where you could streamline the early part to get things to the patient more quickly. Uh, and there are some jurisdictions like Australia that have made that easier in terms of getting trial set up. Uh, and probably, probably there's a case to be made for, uh, in the later stages of development, putting a very high bar on safety and a bit of a lower bar on efficacy. So we know that it's safe, it looks like it probably works. That could save a lot of money and time. And you would have to couple that with post-marketing follow-up. So that do a better job of, it's released now, we're going to make sure we test it in real time. And the benefit there would be that companies would get to revenue more quickly, and patients would get drugs more quickly. But we still wouldn't sacrifice the rigor of understanding how well do these patients really work, how well did these drugs really work in the final patient population. So I think there's, there's probably, you know, some significant improvement that could be done at the back end of this.

At that conference, what are the, who is going to fill those remaining five seats? What are the things that they are going to discover?

That's a great question. That's like anticipating scientific breakthrough and innovation is is pretty tough. Let me just answer this like the, the biggest problem, and I don't think it's going to be one person that understands this, but the biggest problem is for us to get a more complete understanding of human biology and disease. Uh, like if there's one place where, you know, data generation and experiments and maybe even artificial intelligence could really move the needle, it would be in that. But I suspect that's going to be not one person. That's going to be the enterprise of, you know, academia and private sector over the coming decade or decades to put that in place.

And then lastly, imagine you're a freshman who's very interested in biotech, wants to start it, and happens to go to a school where there is no biology department. Yeah, hypothetically, hypothetical, hypothetical. Um, what would you recommend that student do to get themselves up to speed? What resources they look for? Where should they try to, uh, get involved?

I, I think I, I can speak to that because I have no, I never took a biology course. I took maybe one. And my solution to that was sort of twofold. One is that I, I found, uh, work where I could contribute that was adjacent to biology. So I spent, you know, the first 20 years of my career working on building engineering tools, really, that could help enable biological experiments, fundamental and practical. And that gave me the opportunity to, um, rub shoulders with scientists of a caliber that I had no business working with because I brought something new to the table. So that was, that's part of the strategy. That's kind of post-school. You know, in hindsight, I also think I, and I, I learned biology, bio-mosis. In hindsight, I think you could pick up a few books and with not too much effort, pick up most of the basics. Um, and this is going to be a little, uh, maybe contentious if ever this gets out, but my, my view has been, nobody understands biology so deeply that you can't get a working knowledge of a certain area with relatively little work. That is not true in every discipline, but it is true in biology once you have the, the language and the fundamentals. And the biologist will hate to hear that, but I think that's true.

Say, I'll let someone else ask about big pharma, but thank you very much. Thank you for coming and giving this very insightful talk. Um, my question is about, um, how, so in my mind, um, the hatred towards big pharmaceutical companies is geared more so towards, um, the oxycodone manufacturers and T and companies like that, less so than the insulin guys, although there's some hatred towards the insulin guys that I don't personally agree with. You know, I, I do think that, you know, the regulation on opioids and other addictive painkillers should be increased. And I think that big pharmaceutical companies are too financial, or too financially invested in getting these out and selling it to people that are getting addicted. So I don't know, you don't like the hatred against big pharmaceutical companies. I wondered if you thought this was justified.

Me, not even a large number. There are a small number of, uh, quite well-covered, you know, notable, uh, misdeeds by actors in the industry. And so, like, we could list a few. You know, the opioids are one. Drug pricing, hiking things up. And these have, these are the things that seem to capture the media. But, you know, I think maybe particularly important for, or appropriate for, for this school, there's a huge danger in painting a group with a broad brush. Right? Like when I, when I see politicians stand up and say, oh, we've got an an opioid epidemic, we're going to make big pharma pay for it. That is insane. Right? There are, there are some, there are some companies that were complicit in that, perhaps even criminally. I don't know the details of that case, but it certainly isn't the entire industry. Right? It's, it's like saying, anyway. So, so to me, it's about, it's about looking at the whole. And if you look at the whole of the industry, right, and the amount of good that is done, and the odds against which they do it, and the minuscule chance of reward, and you hold that up against the few bad actors that we rightly should call out, uh, you get a very different view. And so to me, it's, it's a bias of negative news and, you know, an animus against against industry, and in particular, the industry of selling drugs. Because in most people's mind, they also don't connect, they don't separate the activity of, like, the question of should you pay for drugs for people that are making drugs versus should people have access? That's another important problem, but they're not the same problem, right? Those are two different discussions.

Thank you. Yeah, thank you for your time. I was wondering from coming from the startup perspective, I'm not too well-versed in biotech specific VCs. But what suggestions would you give to, um, people on the finance side in structuring deals so that you don't end up with situations where they're just looking for an exit and just, like, selling to an acquirer? How would you, like, structure debt agreements, if, like, that's one example, so that you can have more companies, um, that are scalable, that end up not just being eaten up by a bigger player?

The way I would think about, I think you're thinking about that in a bit of a, in a way that I, I might adjust a bit, right? So if you, if you're a startup and you're going to raise money from a venture capital investor, you should recognize that they're running a business, and you are running a business, right? And their business requires that they raise funds from their LPs, that they invest it, and that they get a return. Uh, and that, you know, that's not nefarious, that's, that's how their business actually works. So the challenge is not in, you know, it's not how you structure it. The challenge is in making sure that, hey, I've got a plan that I can execute on, and in executing my plan, it's going to be compatible with your business model. Uh, and if that is not the case, then you need to figure out another way to finance it. Because if you're, if you're fundamentally at odds, right, if you've got, if someone's given you $50 million and they need an exit in five years, and your plan is, I'm never going to exit, like you're going to have a problem for sure, for sure.

Howdy, howdy. Um, could you clarify a little bit on the comment that you made, like when you account things correctly, the ROI for producing new drugs is negative? I would assume, like, since, you know, your company right now, you guys are producing two new drugs, I would assume you plan to make up money from those two drugs. What are the, what are the particular things you guys are doing to make that different? And then, um, why is that ROI so, why is it negative? Is it just because of how much cost goes into producing the drugs? And what makes that cost high? We, uh, some of it might be the regulations, or like, is it, is it really the problem of creating a drug is just that difficult that it requires the, the 10-year long track of like doing R&D? Well, okay, from start to actually making any money? Or, you know, uh, I think I've heard Eric say several times, and he's exactly right, like this industry doesn't deliver value to society until someone gets dosed with an actual product. And that, uh, we work in industry where there's 10 years between the concept and that actually happening. Um, so, you know, first, the first part of your question, when I say that the return is negative, there's lots of ways you can calculate that. It's actually hard to calculate that. Maybe just as a first, first pass, if you just looked at, you know, public companies and the amount of money that goes into to fund all of biotech, right, and then you looked at, you know, the total value creation, you would find that it's negative. Um, and that doesn't mean that there aren't giant winners. Like biotech is, uh, biotech is probably the most, uh, power law driven enterprise that there is. If you, if there have been a 100,000 drugs that people started programs on, you know, all the value is captured in the first 100, and probably a big chunk in the first two. Like that, that's the nature of this. So, uh, really big winners and mostly all losers is how biotech works. Now, now there's lots of reasons why that is, and we could have, like, you could write a PhD thesis on all the incentives and capital and science and everything else that goes with it. Um, but your question was, how do you plan to beat that? And I really think it can be beat because there's a lot of mistakes that get made in where you allocate capital. Um, so maybe I'll take a little bit of time here. So if you're a biotech and you start a company on a drug and you go public and you have a drug, and now the data is not looking that great, you just keep running that drug because if you quit that drug, the company is done, right? So people, you know, because you're so concentrated on one thing, you end up having blinders. It's like a cult of a molecule. And even a real practical, you know, capital access problem that makes you continue to move things forward. That's, that's one of the problems. Um, you know, if another problem is that many of the drugs that get started get started by people who don't understand the competitive or commercial landscape and have no intent of ever actually manufacturing it because they know someone else is going to buy it. So then their framework is not, am I making a drug that's going to make a difference for people? The framework is, can I make something that I think someone will take off my hands? That happens a lot. And there are, there are many acquisitions where a big pharma company spends, you know, $10 billion, $20 billion, and it's a complete bust. So really no value was generated for patients, but someone, you know, was able to get a good exit on that because they anticipated what someone would want. And a lot of decision making gets done like that. Um, I'm, I'm not saying that we have this all solved. But what we're trying to do is create a framework where we are, uh, able to take many bets so that we don't fall in love with anything or we don't have to fall in love with anything. And then always hold up very explicitly what we know and what we don't know along the dimensions that matter. And the dimensions that matter are, will it work? That's a science. When it gets there, will people care? Is it differentiated? And does it solve a big problem? And in order to get it there, is there a path with our resources and expertise that would allow us to see it through? And when you start to hold things up like that, you start to see where the mistakes are, where where the uncertainties are, and you can be more rational in deciding, hey, we're going to run it to here because we get to flip the card. And if the card goes the wrong way, we're going to kill it because we've got something else behind it. And I do think if, if done right, and if you can pick the right opportunities, the success rate can be well, well higher than an order of magnitude better. And there are examples of this. I, I think, you know, companies, I mentioned Regeneron, their success rate is at least 10 times the industry in bringing programs forward and getting them approved. So it's, you know, you can do better that way.

Thank you. Thank you for coming here. A lot of students here at UATX are here to change the world and make an impact. And wanted to, um, hear what would your advice be for someone who wants to create true value and positively impact people in terms of laying a foundation of skills, experiences, beliefs, whether it be in biotech, by learning, by systems engineering. What skills should we accumulate? And the other question I had was, when it comes to long feedback loops, so these decisions that have ripple effect, second, third order effects, what are mental models or ways in which we can, uh, more rationally, pragmatically, and prudently kind of navigate that?

With the more rational understanding, the first question was, uh, what for someone that wants to make a big impact in the world, what skills? Uh, obviously, that, that, that's a big question. Um, I think almost by the breath of that question, I think it's hard to answer it with a specific because you could make an impact in a variety of different domains. Maybe, maybe I'll, I'll try, um, you know, imparting a philosophical idea that that I think is is quite valuable, um, and maybe, you know, resonates with the great books and, uh, philosophical underpinnings here at the institute. Uh, there's a book by James Allen called As a Man Thinketh, and it's a, a very short, beautifully written book. And it basically, uh, communicates a philosophy that, uh, if you want to achieve something in the world, that you should not be looking for the path for that in an outward way. Meaning that it's not about tactics, and these are all important, but tactics and the person I talk to and everything else. I think particularly early in your career, you should ask yourself, if this is the impact I want to have, if this is the company I want to build, if this is the position or the, you know, the good that I want to do in the world, what does the person to which that naturally flows look like? What are the character traits? What are the, uh, the experiences? Uh, what is the knowledge? Right? And to, to take, take the view that almost on a leap of faith, that if I can, if I can work on myself to become that person, the path will open up to me over time. Now, that's, that's not a complete idea, but it is, I think, it's a philosophy of power because it puts the, it puts the responsibility on you to become the person that can accomplish that thing, instead of looking for, you know, the quick fix or the quick path to getting that.

Thank you. Uh, thank you so much for your wonderful talk. If you're a, um, a young student at a university and you have an idea for a biotech project, for example, but you don't have access to the, um, proper, uh, credentials or infrastructure to advance that idea, how would you go about furthering that idea?

If you're an undergrad, I, I think you're exactly, it's really hard to boot up. Like, tech is hard. It's really hard to boot up biotech from scratch because it takes a lot of capital. I would try to find, um, an entrepreneurial professor or someone else who has, uh, got the expertise of pulling together companies or even, even maybe, you know, the infrastructure and the capital to get it going. Uh, spend time with them and try to get them convinced that this is, this is an idea worth pursuing. And if not, understand why. And then you've, you've had a boost there. Um, we had a conversation with with some students, uh, earlier today, and I, I made the point that there's a lot of appetite to go into entrepreneurship. And I think a lot of it is driven because we see the successes of the, you know, the 18-year-old who started the company and it becomes the giant winner. And we don't see the 100,000 other ventures like that that struggled to ever get there. Uh, and it's a very hard thing to boot these things up from nothing. So early in the career, finding a way to get close to and work in an interesting enterprise where you're going to get exposure to the people and the ideas and the ways of working is to me by far the smartest choice. Uh, recognizing that that is not going to be the venture that's the education that sets up the thing you're going to do in the future. And to give you time, uh, to pick up skills and build a network, build some power, uh, and also, you know, pressure test your ideas. And I suspect having, if, if you come out of undergrad, you spend five years working in a high-tech company, the quality of your ideas after that are going to be so much better than they are when you come out, just by virtue of having been exposed to M to much more.

Thank you. And I, a follow-up question is, uh, what sectors of biotech do you think are, um, most, um, susceptible to innovation right now?

Susceptible to innovation, uh, in a positive sense or a disruption sense? In a positive sense. Like, which sectors of biotech do you think, uh, progress can be made? Okay. So, well, there's, uh, there are some really big open questions. Uh, I, I mentioned before, a lot of it has to do with understanding. If we knew the targets, we'd be able to go do them. And I'm a little biased here, but I, I do believe that, um, antibodies. So, so antibodies are, you know, natural molecules. They have the property that they naturally engage with the immune system. They are recognized by the body as self, so they're not rejected. And they are the best thing out there to specifically interact with another target. So antibodies as part of therapeutics is exploding right now. So there, you know, in, in 1992, or so, I think that's about right, um, when RX, maybe it's later than that, RXin might have been even later, anyway, went from zero to about $280 billion dollar market in that time. Much of that was on simple antibodies. What you're seeing now, that's the next wave, is, uh, bispecific antibodies, antibody drug conjugates, multispecific antibodies, radioisotope antibodies. There's a, a Cambrian explosion of modalities that use the advantages of antibodies in unique ways. I think that will be the next big wave of innovation, not just in biologics, but in therapeutics, because you can see a lot, you can see a lot of potential there.

Thank you. As a Man Thinketh is a great book. And a big part of your speech was about how biotech is so important because it can help us resolve our sicknesses and our diseases. And I'm wondering if you have any moral, you know, dilemmas about as science and technology advance, biotech potentially infringing upon our more human qualities? Say, a pill that makes us happy 24/7, you know, where do we draw the line between getting rid of diseases and then, you know, getting rid of our humanity?

It's an easy question. You know, the pill that makes you happy all the time, if that came with, as I suspect it would, a dramatic drop in productivity and ambition, would be a great evil. So I, I would certainly, you know, draw the line there. Um, although I do think that, you know, people that suffer from chronic depression, you know, ways to help them and get, get them be more productive would be useful. Uh, it's an interesting question, like, but for, it's, it's perhaps more theoretical than practical at least today. Because today, when you look at what people are actually developing, uh, it's black and white. Right? Like you've got someone that's got got a fatal tumor, a terrible autoimmune condition, uh, blindness, degenerative bone disease. These are, these are problems that no one believes are, uh, that that everyone agrees would be, would be good to get rid of. Right? Like relieving human suffering and saving lives is as pretty close to an unalloyed good as you can find. Where we're starting to tip into it a bit is like enhancement. And that's starting to happen. Um, so you could say that, you know, some of the, some of the obesity drugs, you know, maybe there's, maybe there's two sides to that. And there's a next wave where people are talking about, okay, now we've got, now we've got, um, you know, uh, OIC, but we're losing muscle. So now we've got another drug to bring back the muscle as you lose the weight. And you can see how this quickly gets into the place where you are looking for shortcuts, uh, for health, where good practice and discipline and lifestyle would probably be the better solution. And if that's the case, then, you know, maybe, maybe it goes both ways. Uh, some people don't seem to be able to handle that. But on the flip side, uh, you know, if you're, if you're making it so that, uh, if you're short-circuiting the incentives for healthy lifestyle and not focusing on that side, I think that can be a problem. I don't, if I, that's really clear there, but thank you.

Yeah, thanks. He there, I just had a quick question. Do you think that innovation has kicked out the bad actors within the pharmaceutical industry? And how is your kind of perspective on any bad actors that are operating in the pharmace, uh, pharmaceutical industry right now?

I wouldn't say that innovation has kicked out bad actors. Um, I, I'm of the belief there are very few bad actors. And that's not just now, there have historically been very few bad actors. And when these really egregious, uh, things happen, uh, they're almost universally caught. So I, I actually think it's, I actually think it's working pretty well. I, I do not think that, uh, that that is a big problem right now in the pharmaceutical industry.

Okay, thank you. Hello, I have two questions about safety. The first one is, I'm curious when you're developing the drug early on, like before you put it in a person or even an animal, perhaps, um, how do you have any way to know how safe it's going to be? And if so, what, well, how?

So the way the way you would typically do it is, well, first, you've got some understanding of the biological pathway. So there are some things where you know, okay, that's probably going to be a problem if I interfere with it. Others, it seems like it should be fine. Uh, then you go and you check what is known about human genetics. And very often, there are people that might not have the protein that you're trying to intercept with. And if those people are fine, that's also, you know, supporting evidence that it would be okay. Uh, then when you make it, uh, you typically go through animal studies to test toxicity. And you'll do it in a couple animals. Um, for most drugs, you, you want to test it in non-human primates, cynomolgus monkeys, because they're closest to to humans. And you'll go through dose range finding, so go up slowly. And then you'll go to the full, full range. And you'll do a detailed analysis to see, are there any adverse events? After all that has happened, and you've manufactured it, and you've proven there's no virus, you submit that to the FDA. And then the first part of the trial is about addressing only this question about safety. And normally, what they'll do is they'll say, okay, in the primate, you went up to 100 mgs per kg, and there was no adverse event. Well, let's dial that back by a factor of 100. And you're going to start there in healthy volunteers. And so then you'll dose someone at what is almost a homeopathic dose, and then a little bit higher, and a little bit higher, and you inch up over time. Uh, and you know, after, you know, running a trial with, you know, maybe, you know, 10 or 20 healthy volunteers, you have reasonable expectation that this is going to be safe. But then safety continues to be evaluated on every subsequent trial. So you might have a 100 patients in the phase, and you might have a thousand patients in the phase three, and then post-marketing, you'll be watching that as well. Um, so, so the, you know, it doesn't mean that there aren't mistakes that are made. And there are some famous examples. But, uh, you know, the guidelines and what people often characterize as like the regulatory hurdle for this is there for a good reason. Because there are some, there are some examples where a great deal of harm was done because attention was not paid to safety. And probably the, the quintessential example that everyone knows is the thalidomide, which, uh, was developed prior to this type of regulation and was really the prompt for this regulation and ended up causing neuropathies and birth defects and, you know, was just a horror story. So the reason we're here is because bad things have happened. Have we, have we gone a little bit too far, perhaps? Maybe not. But, um, you know, as, as a father of children, if my daughter was the first person to get a therapy, I would want it to have been tested in primates. I would want it to have gone through early clinical testing. Like, I, I would not want to short-circuit that.

Thank you. Um, the second question is about like long-term effects and specifically I'm thinking about like cumulative effects. An example I thought of was like, what if your drug had cholesterol in it? And so it over time it just increased people's cholesterol and they ended up getting blood clots and such. It seems that that specifically would be very hard to detect in a short-term trial, like even a seven-year trial. And it might be hard to detect just in like market observation. So like, what do you think about those kinds of safety concerns? Are they valid? How would you?

I think those are, those are valid concerns. And they are monitored and they are detected all the time for drugs. So, so, uh, like typically you do, you know, two phase three trials. Those could be hundreds of patients. You need a certain number of years. And every single adverse event, like, uh, you know, someone hurt their knee, that gets reported back to the clinician. So everything is looked at and a statistical analysis is done relative to placebo to try to detect within some power of of confidence whether or not there's a difference. Then once a drug gets out onto the market, it is monitored. There's an entire, you know, group, entire group and infrastructure in a company to monitor what happens once it's been used in the real world. And it is not uncommon for a drug to be released and then, you know, a couple years later, uh, there'll be a black box warning because at a rate of one in 500, someone had a serious liver injury. You know, that, that happens all the time. So it's hard to know if you miss anything, right? By definition, you don't know that you missed it. But I think it's, I think the, uh, the FDA is rightly very attuned to safety and they've dialed that very high, uh, as a bar.

Thank you. Do you think gain of function research is a Pandora's Box that we should be opening?

That's a good one. Uh, gain of function research on on viruses. Um, it's clearly a Pandora's box, right? Because we've had an event that stems from it. Um, you know, the defense of the defense of gain of function research would be, uh, it's important to understand what we're looking for when there are circulating viruses, so that we can detect early on those mutations that look like they're most dangerous for them to jump into humans. So that's the, the case for it. The case against it is that you're, you're making something that you know by design is going to be dangerous. And if you don't have that locked down and carefully controlled, uh, you can end up with something like COVID-19, which almost certainly came from a lab. And I think everyone in science, or maybe this is contentious, I think everyone in science knew that, uh, very early on. I would be very, uh, I think we should be very careful about what we do there.

What do you think governments can do, or if you were directing policy from the government perspective, are there, is there anything that can be improved, or do you think that overall we're doing a pretty good job at that?

I don't know enough about the policies to comment on that. It's not really in the question. But, um, I think we have to think about it on two fronts. We have to think about what do we, what do we regulate? And what do we do to try to avoid these mistakes? Like, we also have to be on the other side, preparing for those mistakes, either within, you know, the labs in the US or elsewhere, either by accident or deliberately. Um, and, and there's, one of the things that we've been heavily involved in, obviously, is pandemic response. And, uh, what you see is like, this is playing out again. So if you had asked someone, you know, five years before, is there going to be a pandemic? Who worked in the space, they knew there was going to be. And yet no one was doing anything to get ready for it. Today, we have, uh, H5N1 that's circulating. And, you know, maybe it's not going to be a problem. But it is, you know, it's in all the poultry, it's in cows, people are drinking milk, we've got mutations, we've got cases of human transmission. If this thing tomorrow jumps into people and can, and can spread quickly, and it looks like the risk of that right now is low, but if it does, we'll be sitting here going, what were we doing? Like, we just got off a pandemic, and this is like a flashing red light, and no one is taking any action to get ready for this. Uh, so that, I, I think someone needs to look at that, uh, closely. And, and this is, this is something that requires a connection between government and companies. Government cannot pull this off. There's no way. Companies can't afford to do this. You can't run a program just in case there's a pandemic. But if you actually want to be ready for a pandemic, you need to start working before it's there. And so, so some, some amount of continual refreshment of our arsenal of countermeasures against pandemic viruses or bioweapons is probably warranted. And hopefully, it never pays off.

Thank you. [Applause] [Music]