George Zachary1:02:08
I would think. Because people are like, 'Well, we're gods. You're asking the gods to be accountable.' It's like, 'Okay, we're here to bless you with our lightning bolts. How dare you?' It's like, 'Okay, be accountable.' Attorneys charge by the hour. They don't get paid by the outcome. No, those are litigators. Bill Gurley said it to me one time. He's like, 'There are no consumers in the American healthcare system. There's nobody actually buying the service.' Your employer pays for it. If you had to actually look at the menu and they said, 'Here's what your knee surgery is gonna cost you. Here's your insurance premiums. Here's what's gonna happen to them.' And you were actually making this decision, you might actually say, 'You know what? I'm gonna look on a website like Kayak.' A site like Kayak might emerge, or a price comparison search engine might come out where it's like, 'Here's what knee surgery costs across the country.' And you might say, 'You know what? I'm going to Arizona for my knee surgery because it's $10,000 in knee surgery in New York and LA's $100.' This is one of the issues. There's no price comparison. You want a flight to Tokyo? We do price comparison. So the only place where there's price comparison is in biopharma drugs. If you go to buy Lipitor in Oregon or in Florida or somewhere else, it's all the same price. PillPack. It's all the same price. I heard that PillPack idea and I was like, 'So you put the pills in a pack? I don't take any pills. I don't get it.' The average person about 50 takes three prescriptions in the US. Is that right? Yes. Because 40% of the population has diabetes or is pre-diabetic. It's amazing. We're eating too many calories, mostly too many carbs. We literally in the United States became so abundant, we won so big as a country, that I think the last three years life expectancy went down because of diabetes. We went sideways. We went from 79 to 78, 77. Literally declining with massive progress on science, cancer, healthcare. Healthcare spending is 18% of GDP. We're spending more than everybody, and now we're starting to go backwards. And the reason we're going backwards is unbelievably self-inflicted wounds. Human behavior. Eating ourselves to death. And actually suicide is going up. For young people, it used to be drunk driving and a lot of stupid behavior. Now people aren't driving drunk as much. They're killing themselves because social media anxiety is causing them. So the suicide rates are going up. What is the point of having a society that's so rich? And it's also going up in the 75 and above age group. Significantly. Wait a second. People are 75. They get to retire and enjoy. Because they're alone. So we're literally killing ourselves because people are eating sugar, because families are distributed geographically in the US, and people are alone. So we're in this phase and trend of what I call 'connected aloneness.' What does it mean? It means we're all connected digitally, but we're all alone physically. This is why I like you. And this is a bad trend. It's a terrible trend. It goes against being part of a tribe, being part of being nomadic. But it's easy to be cynical about things like Burning Man, but I think a lot of the reason young people are getting into things like Burning Man and a camp at Burning Man becomes like your tribe when you leave, and they do other stuff, is they realize the value. They get this incredible unlock when they have a tribe of people they hang out with. Our poker group has become super meaningful to all of us. We really love each other in our poker group in a way that none of us expected. It was just to generate gambling. But when Dave Goldberg died, who was a member of our core poker group, it just cemented our friendships in such a very deep way that we're on text message all day long. And when somebody gets accepted into that group, when we become friends, it becomes this otherworldly friendship. It's very strange. It's delightful. I've always believed that the digital world should be involved with the analog world. You can't exist just in the digital world. You can, but you're not going to be happy. You'll be empty. We didn't evolve as digital beings. It's empty calories. You can't feed a human through digital methods. There are some people who believe that, like Zuckerberg, this is gonna be great for him. 'We connect everybody.' It's like, you know what? Connecting everybody is not as good as you and I catching up right now. A great moment for us to be here on this podcast. Part of the reason I have the podcast, I'll be totally honest, I get to see my friends. I get to make new friendships. When's the last time you and I sat for an hour? I miss you too. The podcast for me is a way to spend an hour with somebody who I love. You're amongst a crew. What do you think are the big unlocks in healthcare? What are the things that we could unlock in our lifetime? Hopefully you and I are here for another couple decades. What are we gonna see? What are our kids gonna see? If you break it into those two groups, what could our kids see in the next 50 years? What are we gonna see in the next 20 or 30? What do you hope to see? What do you hope to bet on to make happen?
Well, when I started the bio practice, we talked about using AI, machine learning in combination with biology to develop pharma products, drugs, more quickly. Because right now it takes an average of, well, the range is roughly 12 to 15 years to develop a drug. Why is that so long? It starts with an idea in a scientist's mind of what might work. They have a theory. They have to screen tens of thousands of compounds. By the way, 50% of pharma products come from natural products. So they have to screen tens of thousands of compounds, and then they have to go through toxicity scans in mice. Why can't you use AI and machine learning and say, 'Hey, here's what we've learned from all the human tests we've done, all the mice tests we've done. Maybe when we find a new plant in the Amazon or some new compound from something at the bottom of the ocean, we could just say, 'Hey, what does the model tell us could be them?' And let's have the model come up with some theories as well as the humans. Some people are doing this. Is it working? Promising. It matters what data set you feed it. There's one company that takes 240,000 pictures a second of a cell, feeds it, and they feed different drugs to the cell to see how it responds. So they're continuously testing the cell. There's another company that's a brain organoid company. They're focused on central nervous system diseases. They're building little neural tissue groups to basically work on Alzheimer's and see what happens. You're testing different drugs on it. I'm imagining like the movie The Matrix. Everybody was in those things. We don't have to do this on humans. We'll see it on petri dishes. They take stem cells out of people who have Alzheimer's or some other monogenic disease. You're not going to take the whole brain disease like schizophrenia because it's very complex. But you take a monogenic version of autism or a very specific type of Alzheimer's. Alzheimer's covers a group of diseases. We take the stem cells from those people and we develop neurons that have Alzheimer's. Then we figure out we can see the normal firing patterns, and then we can feed them existing drugs, off-label drugs, natural products, and see if it's doing anything. Can we do it with a hundred drugs a day or a thousand drugs a day? High-speed robotics. It's literally that. A robot feeding this and taking video, and then the machine looks at the videos and tells us which one to use. You have to use pretty high-speed, high-powered microscopy to do it. It's compute intensive and expensive. But then you have to have computers analyze the pictures. You still have to have scientists in the process. Can we take those stem cells and the neurons that are firing wrong and computer model that in the same way we can make a virtual reality environment of this conference room? We make a model of how those behave, then make a model of how these drugs interact and simulate it. Or is it just too squishy? It's not definable in that way now. We can model it, but it doesn't cover a lot of cases. That's why it's better to have something like an organoid. We can build a digital model off of retroactive data. That would be interesting. If you did a thousand of these tests on those Alzheimer's neurons that are firing incorrectly that you made from the stem cells, you say, 'Okay, we put these thousand compounds into it. Here's what happened. Maybe we have an idea for the next 10,000 which ones to at least try next.' A little bit of a roadmap, a path. So that in a way is like a wind tunnel modeling. It's more efficient. So that's a CAD/CAM version of the system. But it's not the real cell. It's not the real system. You still actually have to put it out there and test it and see how it's really responding. But you do better experiments. You can do better experiments, and then you can actually see whether your digital model is matching up with the real-world model. You can further tune your digital model. This is a future that's incredible. They could figure out, 'Hey, we know this compound has some impact on Alzheimer's. We're now gonna get a bunch of Alzheimer's patients to be in a test after you test it on mice to make sure it's not toxic.' So far, there's been no successful drug. There is one drug coming to market that could help Alzheimer's from Biogen. Do you think it reverses it, stops it, alleviates it? What can we see in our lifetime? Back to that lifetime question. In our lifetime, which I'm gonna put at a couple of decades, what could we see? What could we experience? And then what would our kids experience? What would be the best-case scenario? Things you would hope to see happen. Cancer eliminated in our lifetime? Mitigated in our lifetime? Alzheimer's in our... I'm not a believer that immortality is a good thing. This is a philosophy question. We don't want to live forever. I think people being immortal is like a cancer cell. The reason I say that is then we run out of resources on the planet and the universe runs out of resources. Some people make bad decisions, as we know from the Google investment. Old people are a sense. We need a new set of humans to actually advance society with new processes, with new ideas. If people were accumulating wealth in the 200-year age range, can you imagine? We're already dealing with generational animosity, a generational gap where the old people are making decisions about social security or the planet that are terrible for young people. Now imagine we're 200 years divided. They may be holding on to philosophies and ideas that no longer apply. Racism, xenophobia. Part of society moving forward is not that the paradigm dies, it's the people who believe in the paradigm die. So you slow down the entire innovation of society. So that's a belief of mine. Coming back to cancer cells, I don't know if we'll ever stop cancer. Cancer has to do with mutation. Radiation creates mutation. There's radiation coming out of the ground. There's radiation coming out of you. There's going to be some. But the idea that you would know somebody in their 40s or 50s who died from it, that to me is what really bothers me. Kids getting cancer, dying early. Brutal. If someone has a long life that's healthy, gets to be a grandfather or grandmother if they want to, gets to be part of a full family, enjoys their life, that's what I'd love to contribute to, helping founders get there. Part of that is early detection of cancer. I'm focused on investing in that area. Early detection, catching stuff so you can do a 10% cure, right? Detection so you can cure people, not at the 90% stage where you're B-52 bombing them with chemo.