Good afternoon everyone and hello to people all over the world listening to us virtually. Here we are on the sidelines of the UN General Assembly. Or we could say the UN General Assembly is on the sidelines of Atlantic Council programming. But that would be wrong. And welcoming this special edition of Atlantic Council Front Page, our premier platform for global leaders. It's a particular pleasure for me and honor to speak with Albert Bourla, Chairman and Chief Executive Officer of the pharmaceutical company Pfizer. He and his company have been foundational pillars of global health that scale complex science to meet humanity's most urgent needs.
Back in November 2021, Albert Bourla had really emerged as someone whose name people were hearing all over the world, as was Pfizer, as we were emerging from the COVID crisis. And in that month, we presented Albert our highest honor for leaders in the business world for historic achievements during that period. In presenting him the award in Washington, and we had not convened ourselves for a couple of years for that award, European Union Commission President Ursula von der Leyen said, quote, you chose to put billions of dollars at risk because if you didn't try the whole world would pay the price. End quote. That choice, she said, and the vaccine it helped bring to the world, contributed to saving millions of lives today. And this is what we'll talk about today.
Albert confronts another historic hinge point in healthcare: artificial intelligence and its potential to transform drug discovery, diagnosis, and human longevity. And that just kind of scratches the surface of what's going on in your industry. The global context is challenging. Populations are aging. Chronic disease is rising. Cancer remains a persistent challenge. Health systems and health budgets are under pressure. In some parts of the world, declines in development assistance are taking a human toll. At the same time, amazing scientific and technological tools are available to us and they've never been more powerful. So, this conversation will capture all that and is part of the Atlantic Council's broader work at the intersection of technology, data, and global affairs.
So, let's start there. I'd like to begin by asking how the experience of leading the world through COVID compares to the beginning of your experience of leading the world through what Demis Hassabis, the founder of DeepMind, has called the intelligence age. Some people refer to both of these events as revolutions. So put on your historian's cap. I think we've talked about this before that the word revolution is overused. Are we entering a revolution? How would you compare what it will take to navigate this period of time to what it took to navigate the COVID period?
I think the COVID period was very different because it represented an existential threat and zero opportunity. There was nothing good that you could expect out of COVID. The only good thing that you could expect was to find the solution and put it behind us. And I think we did well and the world did well because there was tremendous collaboration and we did put it behind us. Now with AI, it's a very different set of animal here. There are threats but there are tremendous opportunities that are ahead of us. And do I think that this is really something special or just another moment of technological innovation? I think it's really special. I think it's opening a completely new era that can only be compared to the wheel and the fire and the first engine things that really changed society and the way that was operating. And that's what we are experiencing right now.
It's so interesting to hear your comparison. I asked Demis Hassabis the same sort of question and he compared it to the industrial age, the industrial revolution. I noted that the industrial revolution, with all the good it brought and it brought a lot of good, it also brought mechanized warfare, two world wars, it also brought capitalism, communism. But in the healthcare world, let's turn to the...
I think what happened was that it was disruptive.
Because every major big technology is disruptive and changes the status quo. That's why we had all these events. There is no doubt that that can happen also now.
Said four times the impact of the industrial revolution at four times the speed. Is that possible? And talk to me about healthcare. You have said that your ambition for Pfizer is to be the most AI-forward company in the industry. What do you mean by that? And given the rate of technological change, you're a company that measures things. How do you measure that?
I think that AI, as I said, will be extremely disruptive, which means that it will create new realities in the world, which means that it will create new winners and new losers. And the winners will be those that get it right, how to be able to deal with it. The losers will be those that either they get it wrong or they are complacent. So staying on the sidelines, it's mathematically certain that will bring you in a disadvantage. And what we do is something noble. We are making breakthroughs that change patients' lives. It's not that we are not making cars that make life more pleasant or cell phones. We are saving lives of human beings and for us it's of paramount importance. I see it that winning means winning for patients. Now what is the successful recipe to do that? Because as I said, some will get it right, some I don't think we know, but it's high time to make choices. So even in the midst of uncertainty, we are making choices about how to go about it.
For AI, I think we can distinguish two different eras. AI cannot do today everything but can do way more than what we are using it for. Way more. And what is the limitation? The bottleneck is not technological limitations. Technology is there and can do much more. The bottleneck is the ability of organizations like ours to transform themselves into an AI-native organization, to transform themselves into an organization that is completely different in the way that it is structured and operates, because now we have the tools that we can do things much better.
So that means not adapting to AI but transforming through it. Everybody is adopting AI.
Very few have transformed, if any so far, because of AI. But that will be the secret to be able to transform yourself.
So let's talk a little bit about that. Your background is biotechnology focused on reproduction, more or less, not a novel field when you were earning your PhD in the 1980s. How have your earliest encounters with cutting-edge science prepared you for our newest interventions in medical research and development, AI? How much does this resemble periods before but is just accelerated and how much do you actually have to think much differently than you've thought before?
I think it resembles other technological advancements but in a scale and speed that we haven't seen before. I couldn't imagine two years ago, I didn't know that we will reach a level like that. So I think it's, as I said before, it's something different. It's not just one more important moment in the way that technology is advancing in the world. It's really a transformational moment.
So let's talk about the trepidation in the public about AI and how one deals with that. Our Atlantic Council technology programs did an AI commission report. The commissioners represented a large part of the American stock market and they had brilliant recommendations for government for US competitiveness. But interestingly, what they were most concerned about was public backlash, public opinion and turning against AI, which it hasn't done in China, which it hasn't really even done to this degree in Europe, interestingly enough. And then we had, this was not made less problematic by the call upon by Dario Amodei, Elon Musk, Sam Altman for a pause. How do you look at this period in terms of public acceptance? What does what you saw from their pause say to you in your industry?
I think people are getting excited but also getting very worried about it and rightly so because as I said, the disruption will change everything and people are concerned about it. And I think when I first heard Dario going out and speaking about it, clearly I got concerned. It particularly forced me to go and understand what really happened with the OpenAI incident and what the drone, what the agents did. And I couldn't believe it when I realized what these agents did. And clearly there is significant risk because they can act on their own. They can act independently apparently from humans and those that program them and they have a lot of power to do things. So yeah, clearly that's something that is concerning.
Still, I think that the risk-benefit ratio of this technology is very advantageous towards the benefit. There are risks that are very big but the benefits are gigantic. I will do a distinction with nuclear power because many people are saying, look, nuclear is the same thing. Imagine if when nuclear was there we would let it just run without regulation, so that's equally powerful, should do the same. I would say that with nuclear power, the risk-benefit was not that favorable. At best, nuclear could help us have cheaper energy. At worst, can kill us all. With AI, it's very different. At worst, there are risks that can happen but the benefit, that if we get it right, will be new medicines, cancer medicines, will be education for all, could be tremendous, the benefit. So why I'm saying that? Because you can take a conservative stance and say let's put a lot of regulations to minimize the risks. You can take a very aggressive stance that says let's deregulate everything so we can maximize the speed and the benefits that we will see. And as with everything in life, the balance is somewhere in between and I think that's what we need to do.
So I'd love you to get just a little bit more specific. You've observed that medicine is the most, I think you said this, the most demanding test AI will face in the real world, human world. What do you mean by that? And then secondarily, if you're looking at that test in research and development for healthcare at Pfizer, what would you need to see to say AI has truly transformed how medicines are developed? And is there a particular, you mentioned cancer, we also talked about this during COVID that meant some of the breakthroughs then could be applied to cancer. Is there a particular milestone you're watching for? Is there anything you're already seeing?
There are a lot of things that I already see and I can speak about them. They are not, maybe, I mean depends how you see it, they are not as impressive, you know, we discover cancer cure, but they are impressive as to we liberated that many hours of scientists from bureaucracy to the bench and to the studies. I'll tell you how I see that eventually happening. Right? Of course, more medicines faster and better. Right? Now, the development of a medicine takes on average 10 years and from that four or five years is what we call preclinical. So, this is you don't test anything on humans. It is all in the labs, in laboratory animals, on the petri dishes, all of these phases. Obviously this is the less regulated part of our work because once you go to humans the regulations are very, very strict as to what you can and what you cannot do.
The four to five years, I can see a path that will become one, right? Because the pieces on humans, there are limitations that are, let's say, connected with a disease or let's say something which is you need to increase the survival of a cancer patient, that means that the study needs to take three years because that's how when you have statistical significance numbers of people that survive. You can condense that, right? Actually, if anything, you can prolong it because you make the three years four and five. But the limitations, they do not exist. If it is how can I design the molecule, how can I test it in animals, how can I do the pharmacokinetics, the toxicology? If I can do those things in silico, if I can develop the models that I don't have to, I can really speed up things and then still test them very well before I go to humans because the last test will be on animals but instead of doing for five years will be for a few months. That's a very tangible example. Is it going to make it less costly? No. Because in our drug discovery and development, the most expensive part, when I say the most expensive, 80% of the cost is the last three, four years when you go to the big phase three studies in humans. This part of preclinical and animals cost a lot of money but in overall scheme of things is a small fraction. However, time is extremely important in that.
And in the way that we speak in Pfizer, we say it's a very, that we introduced it during COVID, time is life. That's what we used to say to all our people when they were working on the vaccine. We're saying time is life. Every year that you are going to save makes the difference of a father or mother that will be able to see the graduation of the daughter or the wedding of the son or not.
So it's extremely important, right, this one year. So we can save tremendous amount of time in the drug development and discovery.
So looking at the people who are listening to us from all over the world here in the room, either themselves have fought with cancer, family members dealing with Alzheimer's, all the chronic diseases, things that we've had to live for so long. Are you saying that we could really compress the moment that we get to those solutions? And then of course there are orphan problems that there's not enough people suffering them and therefore there hasn't been a lot of focus on it. I've been told that might also be an area where AI can get us to the solution faster.
Yes, I think we can compress the time. We can improve probabilities of success. We can have medicines that we go to the clinical trials of humans and you will see way more successes than what we see right now because when you go to a phase three studies, 60% chances of success and 40% that will fail, right? So you can make that 70, 80%. All of that as they accumulate will mean more medicines much faster and better.
And if you could choose AI to solve one problem in healthcare or one disease, what would you choose?
We do a lot in cancer, Pfizer, with AI right now. The reason is after COVID, Pfizer pretty much invested everything that we made from COVID times two in acquiring technologies for oncology. So that was our biggest bet and right now we spend more, 40, 45% of our research budget goes to cancer. There was a reason why we did that. One was because the unmet medical need is huge. Cancer remains the biggest killer. Cancer remains the biggest scare of humanity. Everybody is afraid that this will happen to them. And the second is not only was big need but science was breaking. So biology was advancing in ways that made us feel comfortable we can make a difference. AI will help us design those medicines much faster and much more effective and particularly now some new technologies that are emerging in cancer where you can program the cancer cells to kill themselves. And in order to do that, you need genetic material or data and huge computational power. These are areas that we couldn't even dream before and we can make that a reality today.
That's terribly exciting. You said earlier that comparing it to nuclear, the nuclear world ups and downs aren't the same. On the other hand, we at the Atlantic Council have a bipartisan commission on biodefense and they've been briefed recently by leaders in the AI world. And they're worried. They're worried. Yes, you could get to cancer faster. Yes, you could solve these things faster, but you might also be able to get to bioweapons faster.
Because for both you need significant scientific work to be able to use science for good or for bad. And as I said, AI is a powerful tool. In the hands of evil people will harm a lot and in the hands of great people will produce greatness. Yes, it is a concern that people can discover a new COVID virus and engineer it in the lab. Can it happen better now that there are the AI tools? Yes.
