Curing All Disease with AI with Max Jaderberg

Summary

StarTalk Radio: Curing All Disease with AI with Max Jodeberg

Episode Information:

• Title: Curing All Disease with AI
• Host: Neil deGrasse Tyson
• Guest: Max Jodeberg, Chief AI Officer at Isomorphic Labs
• Release Date: May 30, 2025

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Introduction to AI in Biology

The episode opens with host Neil deGrasse Tyson introducing the central theme: the transformative role of Artificial Intelligence (AI) in biology and medicine. Tyson emphasizes that while AI has made headlines for outperforming humans in games like chess and Jeopardy, its real potential lies in solving complex biological problems.

Neil deGrasse Tyson [02:07]: "AI was not satisfied. Just whooping our ass in chess and in jeopardy and everything else where it looks like brains mattered, it's now taken over our physiology."

Guest Introduction: Max Jodeberg

Neil welcomes Max Jodeberg, whose expertise in AI, particularly in deep learning algorithms, has positioned him at the forefront of applying AI to biological challenges. Max's background includes significant contributions at Google DeepMind, where he worked on projects like AlphaFold—an AI system adept at predicting protein structures.

Neil deGrasse Tyson [05:51]: "Neil searched his 9,000 images on his computer for the word 'telescope' and it found 'telescope' written in Chinese on a photo taken at an angle during his visit to China."

Understanding Protein Folding with AlphaFold

Max delves into the intricacies of protein folding—a fundamental biological process where proteins adopt specific three-dimensional structures essential for their function. Misfolded proteins can lead to various diseases, making accurate prediction of protein structures crucial.

Max Jodeberg [11:09]: "Proteins are these fundamental building blocks of life... they fold up spontaneously in the cell to create these 3D shapes."

Evolution of AlphaFold: From Discovery to Drug Design

The conversation shifts to the development of AlphaFold, highlighting its evolution from AlphaFold 2, which achieved Nobel recognition, to AlphaFold 3. The latest iteration not only predicts protein structures with near-experimental accuracy but also integrates interactions with other biomolecules like DNA and RNA, expanding its applicability in drug discovery.

Max Jodeberg [21:04]: "AlphaFold2 reached experimental-level accuracy for proteins, and AlphaFold 3 expands to incorporate other biomolecular types."

Revolutionizing Drug Discovery

Max explains how AI, through technologies like AlphaFold 3, is revolutionizing the traditional drug discovery process. Instead of the conventional method of randomly testing millions of molecules—a process both time-consuming and costly—AI enables the rational design of drugs by accurately modeling protein-drug interactions.

Max Jodeberg [22:35]: "We can start actually rationally designing these drugs... instead of taking a million random molecules and throwing them at these proteins, AI can model thousands in minutes."

This shift not only accelerates the discovery pipeline but also significantly reduces the average cost of developing a new drug, estimated traditionally at around $3 billion.

Max Jodeberg [27:17]: "It costs on average $3 billion to create a new drug."

Personalized Medicine and Future Applications

The discussion moves towards personalized medicine, where AI-driven drug design can lead to bespoke medications tailored to an individual's genetic makeup. This approach promises treatments with higher efficacy and minimal side effects, moving beyond the one-size-fits-all model prevalent today.

Max Jodeberg [35:11]: "Imagine a world where we can sequence your particular cancer mutations and generate specific drugs for you."

Additionally, AI's capabilities extend to broader scientific applications, such as engineering bacteria to digest plastics or enhancing crop resilience, showcasing its versatility across various fields.

Max Jodeberg [53:15]: "People are using this to create bacteria with enzymes that could potentially digest plastics... more resilient types of crops."

Challenges and Ethical Considerations

Despite the promising advancements, the panel acknowledges challenges, including the vast chemical space (estimated at 10^60 possible molecules) that remains computationally unfeasible to navigate without sophisticated AI models. Furthermore, ethical considerations surrounding AI's role in drug design and potential misuse necessitate robust guardrails.

Max Jodeberg [25:15]: "We need something that we call a generative model or an agent, which is able to search through that space and come up with molecule designs for you."

Max Jodeberg [54:09]: "You need to think about how to use this responsibly... what you're putting out into the world openly versus what you close off for many safety reasons."

The Future Landscape: Quantum Computing and Beyond

The conversation touches upon the synergy between AI and emerging technologies like quantum computing, which could further enhance AI's ability to model complex biological systems. Max envisions a future where AI, empowered by quantum computing, could simulate entire cellular environments, unlocking unprecedented scientific discoveries.

Max Jodeberg [52:29]: "Quantum computers could simulate small chemical systems more efficiently, enhancing our understanding of molecular properties."

Conclusion: The Dawn of a New Frontier

As the episode draws to a close, Neil deGrasse Tyson reflects on the monumental changes AI is bringing to biology and medicine. With pioneers like Max Jodeberg leading the charge, the potential to cure diseases, design personalized medications, and revolutionize entire scientific disciplines appears within reach.

Neil deGrasse Tyson [55:17]: "We're looking through your lens at the birth of an entire frontier in human physiology. What a time this is."

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Notable Quotes:

• Neil deGrasse Tyson [02:07]: "AI was not satisfied. Just whooping our ass in chess and in jeopardy and everything else where it looks like brains mattered, it's now taken over our physiology."

• Max Jodeberg [27:17]: "It costs on average $3 billion to create a new drug."

• Max Jodeberg [35:11]: "Imagine a world where we can sequence your particular cancer mutations and generate specific drugs for you."

• Max Jodeberg [54:09]: "You need to think about how to use this responsibly... what you're putting out into the world openly versus what you close off for many safety reasons."

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Key Takeaways:

1. AI's Role in Biology: AI, especially models like AlphaFold 3, is pivotal in understanding complex biological processes such as protein folding, which is essential for drug discovery and addressing various diseases.

2. Cost and Efficiency: AI-driven drug design significantly reduces the time and financial investment required to develop new medications, potentially lowering the cost burden of healthcare.

3. Personalized Medicine: The integration of AI allows for the creation of personalized treatments tailored to individual genetic profiles, enhancing treatment efficacy and minimizing side effects.

4. Expanding Applications: Beyond drug discovery, AI's capabilities are being leveraged in areas like environmental sustainability and agricultural resilience, demonstrating its versatile impact across scientific disciplines.

5. Ethical Considerations: The rapid advancement of AI in sensitive fields necessitates careful consideration of ethical implications, including data privacy, responsible usage, and safeguarding against potential misuse.

6. Future Technologies: The convergence of AI with emerging technologies like quantum computing promises to further accelerate scientific breakthroughs, albeit accompanied by new challenges and complexities.

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This episode of StarTalk Radio offers an insightful exploration into the intersection of AI and biology, highlighting groundbreaking advancements and contemplating the future landscape of medicine and scientific research. Max Jodeberg's expertise provides listeners with a comprehensive understanding of how AI is not just a tool for game-playing but a fundamental enabler for curing diseases and redefining human health.

Transcript

[Neil DeGrasse Tyson]

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[Neil DeGrasse Tyson]

So AI was not satisfied. Just whooping our ass in chess and in jeopardy and everything else where it looks like brains mattered, it's now taken over our physiology.

[Gary O'Reilly]

Well, no, you pointed it in a good direction, aimed it at a good place.

[Neil DeGrasse Tyson]

And we're getting somewhere to solve our diseases.

[Max Jodeberg]

Yeah.

[Chuck Nice]

So now it's going to cure us of all disease before it makes us its slaves. Cause you need healthy slaves.

[Neil DeGrasse Tyson]

All that and more coming up on StarTalk. Welcome to StarTalk, your place in the universe where science and pop culture collide. StarTalk begins right now. This is StarTalk Special Edition. Neil Degrasse Tyson, your Personal astrophysicist. Special edition means we've got Gary O'Reilly in the house. Gary.

[Gary O'Reilly]

Hi.

[Max Jodeberg]

Neil.

[Neil DeGrasse Tyson]

Former soccer pro, apparently. Yeah. And soccer announcer.

[Gary O'Reilly]

Yes, definitely.

[Neil DeGrasse Tyson]

And you still do that, don't you?

[Gary O'Reilly]

I do.

[Neil DeGrasse Tyson]

Chuck. Nice baby.

[Chuck Nice]

Hey. Announcing that I know nothing about soccer.

[Gary O'Reilly]

You're in my club.

[Neil DeGrasse Tyson]

Then announcing that you are American.

[Chuck Nice]

American dog. On it. Real football violence.

[Neil DeGrasse Tyson]

So we're talking about AI today. That's a favorite topic. We revisit that often.

[Chuck Nice]

Only. Only the future of the entire world.

[Neil DeGrasse Tyson]

AI Matters in biology.

[Chuck Nice]

Oh, wow. Now that's a big deal. I know, I know.

[Neil DeGrasse Tyson]

Because people thinking about, you know, composing your term paper or winning a chess. But it's got a whole frontier ready to be explored.

[Chuck Nice]

Yeah.

[Neil DeGrasse Tyson]

And so tell me what you and your producers cooked up today.

[Gary O'Reilly]

Okay, so we've been on the case to get these guys involved for some time, but they are so busy. So here we go. I'll say it. I'm made of proteins. Yes, you're made of proteins from strings of amino acids that fold into shapes that put all together form us. But there's a fundamental problem in biology that has implications for all of medicine. How do these proteins fold up? Oh, for this solution, we look to AI and a Google DeepMind tool called AlphaFold. The second iteration of AlphaFold 2 won the Nobel Prize in chemistry last year for answering this very question. Who knew AI was smart?

[Neil DeGrasse Tyson]

Now AI win all the Nobel prizes now.

[Chuck Nice]

Just park them all up, pack them up.

[Gary O'Reilly]

Now, the isomorphic labs, together with Google DeepMind, developed and released AlphaFold 3. Yes, we're on the third iteration, and that was last year. And applied these new AI models for drug discovery.

[Chuck Nice]

Oh, that's great.

[Gary O'Reilly]

All right, so think this through. Could our next generations of treatments be computer generated?

[Chuck Nice]

Oh, yeah.

[Gary O'Reilly]

Oh, by the way, Neil, let's introduce our guest.

[Neil DeGrasse Tyson]

I will. We've got Max Yoderberg. Did I pronounce that correctly?

[Max Jodeberg]

Yeah, you got it. You got it, right?

[Chuck Nice]

You say.

[Max Jodeberg]

Yeah, let's hear you say me say it. Yeah. Max Jodeberg, he was practicing. He was practicing.

[Neil DeGrasse Tyson]

So you studied AI at Oxford.

[Max Jodeberg]

That's right. That's right.

[Chuck Nice]

That's a community college.

[Neil DeGrasse Tyson]

Oxford Community College. That's exactly right. In Oxford, England. Yes. So specialized in deep learning algorithms. I got your little bio here for understanding images.

[Chuck Nice]

Nice.

[Neil DeGrasse Tyson]

That was a big advance when. When a search can go into an image. I thought, you know, I died and gone to computer heaven when that started.

[Max Jodeberg]

Yeah, yeah. I mean, you know, this. This was 10, 15 years ago, back before AI was cool, right? Where, you know, you talk about AI and it's something from a sci fi book. But understanding images and videos was like the big thing at that point in time. We couldn't actually do that very well.

[Neil DeGrasse Tyson]

I searched my 9,000 images on my computer for the word telescope and it found telescope written in Chinese.

[Max Jodeberg]

That's crazy.

[Neil DeGrasse Tyson]

On a photo taken at an angle in one of my images when I was visiting China.

[Max Jodeberg]

This is it. During my PhD, we took all of the BBC's back catalog.

[Gary O'Reilly]

No.

[Chuck Nice]

And.

[Max Jodeberg]

And we ran my algorithm across it and created a search engine so you could pull up footage from decades ago that had this text or these objects.

[Gary O'Reilly]

That's seriously some archive.

[Chuck Nice]

If you go into BDC when you do that, do you tie. So when the AI is looking at an image, it's not seeing the image the way we do. We're not even seeing a whole image. Our brains, we're really just intuiting an image when we see it.

[Neil DeGrasse Tyson]

Right? Exactly, Exactly.

[Chuck Nice]

That's how we do it.

[Neil DeGrasse Tyson]

But the AI is, it's like a holistic processor.

[Chuck Nice]

It's a holistic processing AI actually sees the image and what it's seeing is pixels.

[Max Jodeberg]

That's right.

[Chuck Nice]

And that really all it's doing is just, oh, this pixel, this pixel, this pickle in this arrangement, that's this image. So do you tie that to language and that's how we search, or is the search just the AI knows the actual image itself?

[Max Jodeberg]

This was like the big breakthrough back then when I was doing my PhD. And this is what deep learning as well is all about.

[Chuck Nice]

Right.

[Max Jodeberg]

You, you can imagine, if you have this image full of pixels, how do you actually code up how to read text from there? How do you tie it to the language of the text? It's unimaginably hard to code that up by hand.

[Chuck Nice]

Yes.

[Max Jodeberg]

So instead what you do is you put these, what they call neural networks. They look at all of the pixels of the image, and you give it lots and lots of examples of images that have somewhere it's got the text in it, and you tell the neural network what the text is.

[Chuck Nice]

I see.

[Max Jodeberg]

And the neural network, through lots and lots of training, starts to work out its internal algorithm to extract the information from these pixels, piece it all together and spit out the actual text or spit out what the objects are.

[Chuck Nice]

Wow.

[Neil DeGrasse Tyson]

So you're currently Chief AI officer at Isomorphic Labs. This is a biology place.

[Max Jodeberg]

That's right.

[Neil DeGrasse Tyson]

Did you have any biology in your background? Formal biology?

[Max Jodeberg]

No.

[Neil DeGrasse Tyson]

No. Okay, so they want you for your AI.

[Max Jodeberg]

That's Right, that's right. So I was at a place called DeepMind beforehand.

[Neil DeGrasse Tyson]

Oh, Google. Google DeepMind.

[Max Jodeberg]

Exactly. I was there for a long. I absolutely love this core AI technology called deep learning. That's what I've been developing my whole career so far. At DeepMind, we were working on some crazy stuff. Learning to play chess and go and beating top professionals at games like starcraft. Back then it was about.

[Chuck Nice]

That was a big deal.

[Max Jodeberg]

Yeah. And because the world didn't know what AI was. So we were trying to prove that this was even a thing. Right. It seems crazy now, but back then it was just proving that this was actually a real thing. But at the core, you know, I love this technology. I want to see it have profound impact on our world. And I was thinking these things.

[Neil DeGrasse Tyson]

That's where it begins.

[Chuck Nice]

Yep, yep.

[Neil DeGrasse Tyson]

That's where the Terminator starts.

[Chuck Nice]

It's always the innocent dreamer who says, this can change the world for such good.

[Neil DeGrasse Tyson]

And it's in my closet now. Would you like to see?

[Chuck Nice]

Exactly. And then it's always like some evil businessman who's just like, with my weather machine, I will one day rule the world, you know.

[Gary O'Reilly]

So apart from that. Carry on.

[Neil DeGrasse Tyson]

Yes, sir.

[Max Jodeberg]

The good thing is there's some pretty strictly good applications of AI that we can drive. Demis Asabis started Isomorphic Labs, spinning that out of Google DeepMind to really think, how can we apply AI to actually completely solve all disease?

[Neil DeGrasse Tyson]

Okay. So it has genetic links back to its origin story. It was in DeepMind. I feel better about that now.

[Chuck Nice]

Yeah.

[Neil DeGrasse Tyson]

Okay. You happy? I'm happier now, yes.

[Max Jodeberg]

So I moved over as part of that founding team to head up AI in this space. And you know, it's been about three and a half years now. Been a crazy journey, but it's fascinating. It's so much fun.

[Neil DeGrasse Tyson]

So you got this AI expertise and AlphaFold spins off this biological application of it. First, tell me the word isomorphic, what does that mean in biology?

[Max Jodeberg]

Isomorphic is this technical term which is, you know, a one to one mapping of space. Right. And the reason we're called Isomorphic Labs is really that we believe that biology is really, really complicated in the world of physics. We can write down equations for physics with maths, and maths is that perfect description language for physics. But you can't really just write down equations in maths for biology, for the cell. It's just too complicated.

[Neil DeGrasse Tyson]

Biology is the most complex expression of chemistry that we know.

[Max Jodeberg]

There's just so many moving parts. Did you just make that up?

[Neil DeGrasse Tyson]

Yeah.

[Gary O'Reilly]

So really we're looking for a Rosetta stone here for the language of biology.

[Max Jodeberg]

Exactly. So what could be that perfect description language for biology? We believe AI and machine learning is that so that there could exist an isomorphism, a mapping between the biological world and the world of AI machine learning.

[Neil DeGrasse Tyson]

Hence the name Gotcha, gotcha, gotcha. All right, so tell us about protein folding. Because when we learn about chemistry, we learn about chemical reactions. And we're not really taught that the shape of the molecule should have anything to do with anything, is just what is the chemical symbol. And when you write down the chemical equations, there's no shape in there. There's just what elements and molecules comprise it.

[Chuck Nice]

And those equations don't really ever represent the three dimensional nature.

[Neil DeGrasse Tyson]

Exactly. You don't even know which if it has handedness. Right. So take us from there.

[Max Jodeberg]

We think about proteins. Proteins are these fundamental building blocks of life.

[Neil DeGrasse Tyson]

Yeah.

[Max Jodeberg]

They're inside of everyone. They make up everything we have basically. And they're made up of what's called a sequence of amino acids. Each amino acid is a molecule. There's about 20 different amino acids. And you put them together in a.

[Neil DeGrasse Tyson]

Long ever or just in life.

[Max Jodeberg]

In life you can have non natural amino acids as well that you can make as well.

[Chuck Nice]

You can make them, you can make.

[Max Jodeberg]

Them and actually use those for drugs. Sometimes you string these amino acids together and that becomes a protein. But they don't exist as these strings. They fold up spontaneously in the cell to create these 3D shapes. And why that's important is that these proteins, they're basically molecular machines. They don't just exist by themselves. They actually create these little pieces of machinery. They interact with other proteins, they interact with other biomolecules like DNA and rna.

[Chuck Nice]

Right.

[Neil DeGrasse Tyson]

That interaction is a shape fitting.

[Max Jodeberg]

Exactly, exactly.

[Neil DeGrasse Tyson]

So these proteins, it's a 3D puzzle.

[Max Jodeberg]

It's a 3D puzzle.

[Chuck Nice]

Exactly.

[Neil DeGrasse Tyson]

3D jigsaw puzzle.

[Max Jodeberg]

And it's not static, which is way.

[Neil DeGrasse Tyson]

Harder than a 2D jigsaw puzzle.

[Max Jodeberg]

And these are not static things. It's not just static puzzle pieces coming together, they change shape so something comes in contact and that opens up something else on the other side of the protein which changes the machine and on and on it goes.

[Gary O'Reilly]

And that's what I was going to ask you. What speeds is this folding taking place? Is it continuous once it folds? That said, but you've just told me. No, it just keeps moving through the whole thing.

[Max Jodeberg]

Yeah. These are really, really complex dynamical systems composed of thousands, millions, trillions of atoms within our cells. Unfolding over the course of microseconds and beyond.

[Chuck Nice]

And this dynasism that you're talking about.

[Neil DeGrasse Tyson]

What word is that?

[Chuck Nice]

Dynasism.

[Neil DeGrasse Tyson]

That's a word.

[Chuck Nice]

Isn't that a word?

[Neil DeGrasse Tyson]

Dynasism.

[Chuck Nice]

I think I just made it up.

[Gary O'Reilly]

Msm.

[Chuck Nice]

Oh, dynamism.

[Neil DeGrasse Tyson]

No, dynamism.

[Chuck Nice]

Dynamism.

[Neil DeGrasse Tyson]

Thank you.

[Gary O'Reilly]

I'm correcting grammar. This is a first.

[Chuck Nice]

This is dynamism.

[Neil DeGrasse Tyson]

Dynamism. That's a kind of dinosaur dynamism.

[Max Jodeberg]

Not dinosaur.

[Neil DeGrasse Tyson]

Dinosaurs.

[Chuck Nice]

Not dinosaur. But the dynamism that you're talking about within the cell, when you look at each one of us, since each one of us is so different, even though there's a general execution and blueprint, we all come out so different. Is that part of the process that you are looking at and mapping?

[Neil DeGrasse Tyson]

I would say, to a jellyfish, we all look identical. True. Okay. They're not saying, oh, is your skin color slightly different or you're slightly taller?

[Chuck Nice]

Yes.

[Neil DeGrasse Tyson]

You're describing functions at a cellular level. Is your job to understand that, or is your job to figure out extra ways to fold proteins that maybe biology has yet to even figure out that can then solve problems that we encounter that the natural universe has not?

[Max Jodeberg]

So.

[Neil DeGrasse Tyson]

Ooh, that was a good question. If I say so much, you're happy with yourself.

[Gary O'Reilly]

Happy with yourself.

[Neil DeGrasse Tyson]

I'm so happy with myself today. Yeah.

[Max Jodeberg]

This is really interesting. We have these little molecular machines, these proteins, and we care about that 3D structure and how they work for two reasons. One, we want to understand how our cells work, because if something goes wrong with that, which is the case for disease, then we want to understand, okay, where can we. Or where do we actually need to go in and start fixing that?

[Chuck Nice]

Right. Well, now we can stop it from actually going wrong in the first place.

[Max Jodeberg]

Exactly, exactly. So that's one thing. And then when we think about, okay, how can we go and fix that? What we're actually saying when we're doing drug design, we're saying, can we create another molecule that will come into the cell and actually start modulating these molecular machines? This drug molecule is going to actually attach to this protein over here, and that's going to cause this protein to change shape, for example, and so it won't operate how it normally does? Or so we stop that protein working or we make it work better. These are the sort of things we do in Covid.

[Chuck Nice]

Reminds me of messenger RNA vaccines that we developed for Covid.

[Neil DeGrasse Tyson]

Yeah.

[Max Jodeberg]

You know, there's so many different types of molecular mechanisms that we take advantage for the drug design.

[Chuck Nice]

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[Gary O'Reilly]

This is StarTalk with Neil DeGrasse Tyson. Other folding proteins generally following a set pattern in the way that they do fold and you're able to map them and when they misfold, that's when you're able to flag that up. Or have I just reinvented something or talked rubbish?

[Chuck Nice]

That'd be cool.

[Max Jodeberg]

No, no, you're onto something so great. So, you know, like the. I mean, the amazing thing is that we can actually turns out, predict how these proteins fold.

[Gary O'Reilly]

So they are modeling that?

[Max Jodeberg]

Yeah, we're modeling that with deep learning, with neural networks. That's what Alphafold and all its generations are all about. And that means that we can actually just take in a sequence of amino acids, knowing nothing about this protein before, and then get out the 3D structure. And normally this would take people months, if not years, to work out this 3D structure.

[Neil DeGrasse Tyson]

So how is it that AlphaFold knows how a large molecule wants to fold? Again, it's gotta know that in some way.

[Max Jodeberg]

It's learnt this from a few hundred thousand examples. So chemists, biochemists, over the last 50 years, they've been working out these protein structures by hand. They've been literally synthesizing protein, crystallizing it, then shooting X rays at this to look at the electron scattering. And from that you can resolve the protein structure. It's a pretty hard process, but people have been doing that.

[Neil DeGrasse Tyson]

That's your way to photograph what the shape of the molecule is.

[Max Jodeberg]

That's your way to photograph in reality.

[Neil DeGrasse Tyson]

With that kind of. It's basically an electron microscope at that level.

[Max Jodeberg]

Yeah, similar. It's like electron scattering. Yeah, exactly. And so people have been doing that for the last 50 years and depositing these structures. And now we've taken all of that data and trained a neural network to go just from the input of what is this molecule description, to try and predict all of that data.

[Chuck Nice]

Right.

[Max Jodeberg]

And the amazing thing is, and this is really remarkable, is that you can then train this on the last 50 years of data. That's a couple of hundred thousand protein and biomolecular systems. But you can apply it seemingly to everything we know about in the protein universe. In the proteome.

[Chuck Nice]

Well, it has proteome.

[Max Jodeberg]

The proteome.

[Gary O'Reilly]

Oh, we like that.

[Max Jodeberg]

Proteome.

[Gary O'Reilly]

So how accurate is Alphafold? An alpha fold? We're on the third iteration with its predictions because AI's been around a Little while, as you've already said. And you're not the only AI tool that's out there. But how accurate is this particular tool?

[Neil DeGrasse Tyson]

Yes.

[Max Jodeberg]

So. So AlphaFold2, right. Was that big jump where we started to get experimental level accuracy for just proteins, and that's what won the Nobel Prize.

[Gary O'Reilly]

You balance it off against empirical, experimental.

[Max Jodeberg]

The benchmark is doing the real lab work itself.

[Chuck Nice]

Right.

[Max Jodeberg]

So alpha two reached that level. Now, Alpha fold three expands from just, just proteins to incorporate other biomolecular types. So proteins with other proteins, proteins with DNA, with rna, with what's called small molecules, which are.

[Neil DeGrasse Tyson]

They go to the neighborhood, they start mixing all that up.

[Gary O'Reilly]

Or maybe not the neighborhood. Maybe that neighborhood gets a little bit of an upgrade.

[Chuck Nice]

No, that's. That's when you make the superhuman. So I know I'm trying to balance the terminator. It's not going to be the terminator, it's going to be the superhuman. And then they're going to be like us and they're going to look down on us and go, you know, why do we need you guys? And that's it. So anyway, you're able to predict these. And have you actually taken any of the modeled predictions and made the proteins?

[Neil DeGrasse Tyson]

Yeah.

[Max Jodeberg]

Oh, yeah.

[Neil DeGrasse Tyson]

Or tell us where you expect these to lead to new and innovative drugs, because otherwise it's just a. It's, it's just a puzzle exercise.

[Chuck Nice]

Yeah, it's a great Lego set.

[Gary O'Reilly]

We want the guests to enjoy this.

[Chuck Nice]

Yeah, it's like, oh, my God, how much that LEGO set cost? Only $10 billion. Sorry, go ahead.

[Max Jodeberg]

Yeah, yeah. So. So. So if you take a particular disease and we think that we can actually solve this disease by modulating a particular protein, the question is how we do that. So we design a drug molecule and we want it to fit to this protein in a certain way. And so this is where traditionally you would have to actually either just guess.

[Chuck Nice]

Or go into that and create, crystallize each one of those combinations and then photograph them and see if it worked. But now you can model it, and the AI can do a thousand of those in like a minute.

[Gary O'Reilly]

Isn't this what the target. Target proteins?

[Max Jodeberg]

Wow.

[Gary O'Reilly]

So if you know you've got a certain target protein, do you not then run that against a list of drugs and think, yeah, this one, drug A works better with this, or maybe it's drug D or whichever letter of the Alphabet you're on. And now we become the sort of detective. And has this alpha fold 3 produced how many clues and how many answers or are we still grappling?

[Chuck Nice]

Yeah. Instead of trying to figure out the drug, the AI actually figures out the drug for you.

[Gary O'Reilly]

Drug discovery.

[Max Jodeberg]

Well, exactly. You know, if you let the guy.

[Neil DeGrasse Tyson]

Speak, we both hear the two of you. Okay.

[Chuck Nice]

We're figuring out this whole industry ourselves.

[Max Jodeberg]

Gary. Yes. Yeah. You know, this is exactly where it's going. So.

[Gary O'Reilly]

Right.

[Max Jodeberg]

We can start actually rationally designing these drugs.

[Chuck Nice]

Right.

[Max Jodeberg]

Traditionally, you would take a million random molecules and you would just throw them at these proteins and see what sticks. And that's how so many drugs have been created historically. You go back further and you're sifting through mud to find these sort of molecules.

[Gary O'Reilly]

Is this why there's been such a low percentage of success rates with the sort of drugs for whatever the problem is?

[Max Jodeberg]

That's part of it, because we don't necessarily understand how these molecules are working. But with something like Alpha Fold 3, you can put the molecule, put the target protein into the system, into the neural network, and you get out the 3D structure. And as a chemist, you can start to understand, okay, how is this small molecule drug modulating this protein? Now still, the problem is, well, how do you find that small molecule in the first place that's going to be good for this protein? It's estimated as like 10 to the power of 60 possible drug like molecules out there. That's 10 with 60 zeros.

[Neil DeGrasse Tyson]

So how many people know what, 10 to the 60?

[Max Jodeberg]

Yeah, yeah, yeah. Don't be rude. Even if you had the perfect alpha fold, you'd have to run that across 10 to the power of 60 molecules, which is just computationally impossible.

[Neil DeGrasse Tyson]

It's unfeasible until quantum computing.

[Max Jodeberg]

And so then what we need is something that we call a generative model or an agent, which is able to actually search through that space, understand that entire molecular space, and come up with molecule designs for you.

[Neil DeGrasse Tyson]

Oh, because the 10 to the 60 is if you just did it randomly.

[Max Jodeberg]

Exactly.

[Neil DeGrasse Tyson]

Right, Right.

[Chuck Nice]

But that's thrown it at any.

[Neil DeGrasse Tyson]

If you don't do it randomly, then you can.

[Max Jodeberg]

Yeah, but randomly is the state of the art method. Right. That's how people do it.

[Neil DeGrasse Tyson]

It's how people currently do it.

[Max Jodeberg]

It's how people currently do it.

[Neil DeGrasse Tyson]

Well, he called it state of the art.

[Chuck Nice]

You're the state of the art.

[Neil DeGrasse Tyson]

Right, thank you. Let's use the word properly here.

[Gary O'Reilly]

So what if protein turns left when you've predicted, when you've mapped it to turn right? Is that when we have issues that Even Alpha Fold 3 has a problem with?

[Max Jodeberg]

Exactly. These are not perfect models at the end of the day, they're very, very accurate, but they will make some mistakes. So you still do currently need to go into the lab occasionally, but the amount of lab work you have to do is so much less.

[Chuck Nice]

Right.

[Max Jodeberg]

And often you can find the area of molecular space where these, these models work really, really well. And we then go out to the lab later down the line, we crystallize these things and we see. Yeah, like this is a perfect mapping of what the model predicted.

[Neil DeGrasse Tyson]

So back to an earlier point.

[Max Jodeberg]

Yeah.

[Neil DeGrasse Tyson]

In the old days, like last month, you, the, the pharmaceutical companies, Big pharma would spend millions, maybe not quite a billion, hundreds of millions of dollars developing a drug. We think that holding aside what might be abuses of pricing, the fact that there's some truth to this first pill cost $50 million. The second pill cost $0.10 because they had to research to get the formula for that first pill. If you have narrowed the search space, then the cost of developing that first pill can be manifold smaller.

[Max Jodeberg]

It costs on average $3 billion to create a new drug.

[Chuck Nice]

Wow.

[Max Jodeberg]

That's on average.

[Gary O'Reilly]

Yeah.

[Neil DeGrasse Tyson]

And so, yeah, when I said $100.

[Max Jodeberg]

Million, you were lowballing.

[Neil DeGrasse Tyson]

Low is lowballing it.

[Max Jodeberg]

Okay. So this is a massive opportunity to like completely change.

[Neil DeGrasse Tyson]

Just like the cost, the speeds, the business model.

[Max Jodeberg]

And the business model as we do.

[Chuck Nice]

That, is it proprietary? So here's my real. Because here's where you would revolutionize. So if I come up with it and I'm. I'm company A, right. It's mine. And I get to determine everything. If you're an AI company and you're just doing this, okay. So that you can sell it, then it's yours. Which one will be. Will make prices lower for the consumer.

[Max Jodeberg]

Our goal is to really redefine this way. You do drug design so it becomes so much cheaper. We have so much more abundance of potential drugs and chemical matter that it really does change the business model and it changes the economics of the space.

[Chuck Nice]

So you can actually revolutionize the cost of making drugs.

[Max Jodeberg]

Yeah, that's where we're going.

[Chuck Nice]

Okay. All right. Is one satisfied?

[Gary O'Reilly]

Is one of the next steps with alpha fold, whichever it's three or maybe the next iteration or so going to investigate why and what drives the misfolding of a protein. So as you can kind of get ahead of even the story of that happening.

[Chuck Nice]

Wow.

[Max Jodeberg]

So. So actually the misfolding of a protein is another thing that, that's what causes some types of disease.

[Gary O'Reilly]

Yeah.

[Max Jodeberg]

Where you'll have a genetic mutation, a mutation in your DNA which will change a particular amino acid in that protein. And so it doesn't fold the normal way it should fold. And so it doesn't function as it normally should as a molecular machine. And so things like Alphafold can help us understand what are those mutations that cause misfolding. And they're called missense mutations. And then, you know, these could be potential drug targets. So we could think about molecules that could mitigate against that.

[Neil DeGrasse Tyson]

If I understand correctly, if you look at the PDR is this thick and what's pdr? The physician's desk reference.

[Chuck Nice]

Thank you.

[Neil DeGrasse Tyson]

Is this thick. So it's the size of an old style Manhattan phone book. Okay. It's very thick, multiple inches across and it's chock full of existing medicines available to the doctor to prescribe. Is it true that 100% of those medicines are interacting with the patient chemically rather than through protein folding? So that if that's the case, does that mean that where proteins misfold, we can't combat it with any kind of folding algorithm? We just prescribe chemistry for your body to handle the impact of that. Is that, did I say any of that? Right.

[Max Jodeberg]

I think that is the majority of drugs, they are chemicals that we take.

[Neil DeGrasse Tyson]

The chemical is not going to fix the fold. It's going to treat the symptoms of the misfolding that happened.

[Max Jodeberg]

We're not changing the mutations of the proteins that could be something like gene therapy, but these are chemicals that come in and will attach themselves to these proteins and somehow mitigate the, you know, something like a misfold or it'll change an interface, change how these molecular machines work.

[Chuck Nice]

That's why.

[Gary O'Reilly]

Is there a particular disease Isomorphic labs are focusing upon right now? Or is this a more broad spectrum? Let's do, let's, let's go for proteins and cherry pick out certain things or we'll be really looking at one particular.

[Max Jodeberg]

The technology we're creating is really, really general. We want to be able to apply this drug design engine on any protein, any target, any disease area that comes our way. Now saying that, you know, practically as a company and you want to focus on a particular area, we're focusing at the moment on, you know, a lot on cancer and a lot on immunology.

[Chuck Nice]

Of two biggie, two biggies and the two that probably lend themselves best to what you're trying to accomplish actually.

[Gary O'Reilly]

Okay, the question everyone's going to want me to ask right now, that's watching this and listening to this, is how you getting on.

[Max Jodeberg]

Would, I mean, it's going really well, to be honest. We're seeing these algorithms actually change the way that we're able to do drug design. We're able to discover completely novel chemical matter against some of these targets that people have been working on for even over a decade. So really, really hard stuff. Making amazing progress still really early in the company, but it's super exciting.

[Chuck Nice]

And have you sent anything to be photographed yet?

[Max Jodeberg]

We send some things for molecular photographs.

[Chuck Nice]

Yeah, yeah. I know you're not allowed to talk about it. I know, I get it.

[Max Jodeberg]

But we're all very happy.

[Chuck Nice]

Okay? We're all very happy. Listen, I'm with you. I'm picking up what you're putting down. That's cool.

[Neil DeGrasse Tyson]

Yeah. But so I see this work as fundamental research so that you publish a result. You publish the image as they published the image of the DNA molecule to know that it was a double helix.

[Chuck Nice]

Exactly.

[Neil DeGrasse Tyson]

That becomes public knowledge at that point. So someone with tools access to alpha fold 3. Would any company have access to this once you have published the blueprint for.

[Max Jodeberg]

It in drug design? Often these blueprints come out in the patents. So when you're going to go into clinical trial, you need to patent these molecules and in those patents you'll have a lot of data around the molecules.

[Chuck Nice]

The formula I was talking about earlier.

[Neil DeGrasse Tyson]

Yeah, yeah, yeah. Okay.

[Chuck Nice]

Yeah.

[Neil DeGrasse Tyson]

All right. So the immune system, the cancer, these are leading causes of maladies in this world. What of the genetic disorders that affect one in a hundred thousand people?

[Chuck Nice]

Wow.

[Neil DeGrasse Tyson]

You bring them together, there's enough of them, you know, they'll fill a stadium in the world. But that's so uncommon as to not really trigger anybody's interest.

[Chuck Nice]

Yeah. It's also not profitable. Well, yeah, because you don't have enough of a market to sell the drug.

[Neil DeGrasse Tyson]

Right.

[Max Jodeberg]

I mean, you know, it's exactly that. That point, Chuck. It's traditionally, it might not be that attractive commercially to go after, you know, very small patient populations, but in a world where it's so much cheaper, so much easier to get to these drug molecules, then that opens up like all of this space.

[Neil DeGrasse Tyson]

And the cheaper it is, the, the easier you can justify going down that risk list.

[Chuck Nice]

Down the risk list.

[Max Jodeberg]

And this is a big guiding star for us. Like that's, this is why we're doing this.

[Chuck Nice]

That's beautiful.

[Neil DeGrasse Tyson]

I see what you did there. Guiding star.

[Chuck Nice]

Yeah, you know, it'd be great though.

[Gary O'Reilly]

He's picked up in the environment. He's not sitting. Why is chief AI Officer?

[Chuck Nice]

I'm interested to how active the company is in shaping policy around what you're doing because there's going to be a great deal of legislative policy that is going to be tied to what you're doing. All of the patent implications, there's going to be, you know, research implications, there's going to be a lot of things tied to this.

[Max Jodeberg]

Yeah, yeah. I mean, we've been talking in this conversation about drug design, but then once you've designed the drug, you've gotta go into patients in clinical trials and that's a really long process.

[Neil DeGrasse Tyson]

Yeah, that's why we have mice.

[Max Jodeberg]

But even these mice models, they're not actually very predictive. Like you do all these studies in mice and then they don't, you know, it doesn't translate into success in people.

[Chuck Nice]

Right.

[Gary O'Reilly]

You gotta go up the evolutionary scale and then get to the human bit.

[Max Jodeberg]

Yeah, exactly. And so there's, you know, you can imagine a world where we can design loads of new drugs. We've got to be changing the way that we're doing clinical trials, you know, how we can actually get these drugs to patients who really, really need them in a timely manner. So I think there's a lot to be done and like rethought.

[Gary O'Reilly]

There is the ultimate goal for Alphafold and I think medical science as a whole to be able to bespoke medication for you as the individual rather than the broader spectrum medication that we find ourselves with all the side effects. So are you able to then design a drug or a medication that has zero side effects and works? Exactly.

[Max Jodeberg]

For me, this is the goal. Right. This is what we're shooting for. You know, imagine a world where we can sequence your particular cancer mutations. Right. And then based on those, your individual mutations be generating specific drugs for you.

[Chuck Nice]

Right.

[Max Jodeberg]

That even these are like, you know, 3D printed or something around the corner.

[Chuck Nice]

Okay, yeah, this is.

[Max Jodeberg]

We know that.

[Chuck Nice]

Yet we're in the very nascent stages of that right now with immunotherapy for cancer treatments and.

[Neil DeGrasse Tyson]

But how many of these yet to be cured diseases lend themselves to solutions that involve protein folding? And how many are just plain old, old fashioned chemistry?

[Max Jodeberg]

Proteins make up like pretty much all of our molecular machinery. So there's a class of disease which is due to misfolding, but then there's many, many other diseases which are due to, for example, a protein not being expressed properly or, you know, a cell going wrong in a certain tissue.

[Neil DeGrasse Tyson]

If I have a bacterial infection, I give myself antibacterial chemicals and then I'm done. Do I need you for that?

[Max Jodeberg]

But those chemicals are interacting with the proteins in the bacteria okay, so proteins are the fundamental machinery and the chemicals which are drugs are modulating those proteins, whether it's like in our cells, in bacteria.

[Chuck Nice]

All right, so it's basically everything you're talking about is all happening on the cellular level.

[Neil DeGrasse Tyson]

If what you're describing is happening inside of cells, proteins doing their thing, their 3D jigsaw puzzle, and you have a solution for that, a remedy. You have to get your remedy inside the cell to interact with that folding the delivery system. And how do you do that, other than through like a Trojan horse virus or something? Because viruses get in there pretty on command.

[Max Jodeberg]

Yeah. Well, if you think about the drugs that you take as pills, drug design is really hard because it's not just about targeting these proteins. We've got to get them to the right place. We might want a pill that you take. So you take this pill, it's gotta be absorbed by the body, so it's gotta be soluble.

[Chuck Nice]

Right.

[Max Jodeberg]

It's gotta go through the gut wall, it's gotta go through the bloodstream, to the particular tissue type, the cell type you care about. Then it's gotta go through the cell membrane to be able to actually target, maybe a target which is within the cell. So you need all of these properties in a single molecule. So we're actually designing these molecules not just to hit the protein, but also to be soluble, to be cell permeable. There's so many different factors. And then you don't want this molecule to be toxic, so you want it to hit the target of interest but not hit anything else.

[Neil DeGrasse Tyson]

Right. So I can see how a molecule gets through the cell wall. Yeah, a simple molecule, but a full up protein. Red blooded protein. How's that getting through the cell wall?

[Max Jodeberg]

Exactly. There's different types of drugs. Some are what we call small molecules, things you could take as pills. Others are made from proteins there. They're often things that you would inject directly inside. So you. And some of those might be cell permeable. There would be things like peptides, but often these, these protein based drugs, things like antibodies, they're injected but they don't go in the cell. They're just interacting with proteins on the surface of cells. So you don't need that permeability. So it really depends on what your target is and how do you want people to be able to take that drug. Sometimes a pill is the best thing, but actually sometimes injecting is the best thing.

[Neil DeGrasse Tyson]

And remind me what a peptide is.

[Max Jodeberg]

A peptide is a really small protein. So you've got full blown proteins which are these big molecular machines. And then you've got small proteins. Small, made up of, you know, five to 50amino acids.

[Neil DeGrasse Tyson]

Loads of peptides.

[Max Jodeberg]

Loads of peptides. They're smaller, so sometimes in some configurations they can get through the cell wall.

[Chuck Nice]

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[Gary O'Reilly]

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[Gary O'Reilly]

So with this computer science, are we upending chemistry as we've known it and are we going to find it kind of moving off with AI?

[Neil DeGrasse Tyson]

With AI?

[Gary O'Reilly]

The AI is it then sort of moving into the other sciences? Are we going to just see it stick in one particular area?

[Max Jodeberg]

Chemistry is always going to exist. To me. It's like any field of science at the moment. Doing science like chemistry without maths. You wouldn't think about that now. And it's going to be the same thing with AI. It already is in my mind. You just wouldn't do chemistry without AI. You wouldn't do biology without AI. It's just that fundamental tool that allows us to understand the world better.

[Chuck Nice]

So chemists will not one day be like coal miners. Just like I remember my grandpapa Used to go into the lab.

[Gary O'Reilly]

So going back to an issue. Chump.

[Neil DeGrasse Tyson]

He comes home smelling like chemicals.

[Gary O'Reilly]

Who's actually going to be able to Access Alpha Fold 3 or AIs of this iteration? Is it exclusively Isomorphic Labs or this comes out in license.

[Neil DeGrasse Tyson]

I want a home kit. That's it. Exactly. Right, right, right. My DNA goes in, there's an Alpha Fold going on, out comes a pill and I take it. And I don't even need you at that point.

[Chuck Nice]

That would be so cool. You just finger prick or put your finger on a sensor or something and it figures it out.

[Neil DeGrasse Tyson]

You make your own pill at home.

[Max Jodeberg]

Yeah, yeah, look up the Theranos story for that one.

[Chuck Nice]

Wow. That's the woman that went to prison. Right.

[Max Jodeberg]

But no, you can access AlphaFold. So if you search for Alpha Fold Server, there's a whole web based system where you can, you can fold proteins there for, you know, academic use. It's really cool. So you can just put your system in, get the 3D fold out from Alpha 3, download it. Yeah.

[Chuck Nice]

Oh, cool, man.

[Gary O'Reilly]

I mean, how far away are we from modeling an entire human being? Which I suppose touches onto your fears.

[Neil DeGrasse Tyson]

Modeling or creating?

[Chuck Nice]

Either or once you model, the next step is creating.

[Neil DeGrasse Tyson]

Yeah, that's true.

[Chuck Nice]

That's all there is to it.

[Neil DeGrasse Tyson]

That's true.

[Max Jodeberg]

That's the dream. We kind of need to work up the scales here. So, you know, we can model how two atoms interact, we can write down those equations. We can simulate small atomic systems with things like AlphaFold. We get into bigger atomic systems, things on the scale of like multiple proteins. Now we've got very, very accurate Alpha three. Maybe we can actually bootstrap of that to get to more sort of even bigger systems, what we call pathways. How all of these things interact.

[Neil DeGrasse Tyson]

It's only just now clicking within me because you can look up in a book the tables of action potentials for the interactions of atoms and molecules. And so you'd have a very good sense of which molecules will combine. Is it exothermic? Is it endothermic? But these are atoms and molecules. And as powerful and as convenient as that is, that's just the first rung in this ascending ladder of complexity that you are gaining control over.

[Max Jodeberg]

Yeah, and there's trillions of atoms within a single cell, let alone the whole human body.

[Chuck Nice]

Right.

[Max Jodeberg]

It's just unfeasible to simulate the whole thing. But what you can do is you can, you know, we do have good measurement techniques at different levels of scale. So we can measure things like protein Folding. We can measure the amount of protein within a cell. We can measure the number of cells of certain type within a tissue. And so we have these.

[Neil DeGrasse Tyson]

The bigger it is, the easier it would be to measure.

[Max Jodeberg]

So we have these little windows into this sort of microscopic world. And then we can use AI to sort of fill in the gaps and bootstrap off the stuff. We can do, well, the atomic level and start building up that scale of modeling, if that makes sense.

[Neil DeGrasse Tyson]

We can rebuild them.

[Chuck Nice]

I read this article like God knows how long ago.

[Neil DeGrasse Tyson]

How long did Jack read the article?

[Chuck Nice]

Because, you know, God. Anyway, it was talking about when a fertilized cell starts to proliferate and become a person. And basically what it determined, what the scientists determined at that point, and this is many years ago, is that the only way they could describe it is there's a bunch of noise. Like, there's just a bunch of noise. We can't really see anything. We can't make sense of any of it because it's just basically, if we were to look at it as data, it would just be noise. Are you able to pierce that veil and see into that?

[Max Jodeberg]

I mean, we haven't been looking at that specific thing. Okay, but this is where you start to understand more about, you know, a really granular scale. And then you, you can integrate that and create these sort of, I don't know, coarser measurements and coarser predictions. This is what we do in lots of areas of science. Right. We don't simulate the whole universe at the atomic scale, but we find these rules of thumb or ways to describe sort of broader collections of molecules. And that's what we can start to build up and actually learn with these neural networks.

[Chuck Nice]

Cool.

[Gary O'Reilly]

So question on behalf of Chuck. Could Alphafold discover a hallucinogenic that could make him see God or any other deity or being?

[Chuck Nice]

Thank you for asking.

[Max Jodeberg]

Welcome.

[Chuck Nice]

I would like a very real answer, please.

[Max Jodeberg]

You, you can go on the AlphaFold server and try that out.

[Chuck Nice]

Okay.

[Gary O'Reilly]

All right. Invitation.

[Chuck Nice]

Hey, listen, I'm all about it.

[Gary O'Reilly]

So we've looked in previous shows, talking to biomedical engineering, and if we are to travel off world and deep space, we are probably going to need different upgrades for us to be able to do that. Are we going to be able to, with AlphaFold or AI like this, be able to upgrade ourselves to make this sort of deep space travel or, or.

[Neil DeGrasse Tyson]

Upgrade ourselves for anything? Any need that we're over there?

[Gary O'Reilly]

Yeah, you know, yeah, now, now we're.

[Max Jodeberg]

Sort of beyond you know, solving disease into like, actually, can we enhance ourselves Right, Yeah. I don't know. I think like there's. There's probably potential, right, to. To think about creating chemical matter that we can take or ingest that.

[Chuck Nice]

I mean, aging alone would be.

[Max Jodeberg]

Aging huge. Exactly.

[Chuck Nice]

Application for this.

[Max Jodeberg]

I mean, there's crazy research on aging.

[Chuck Nice]

Aging is basically cell. And if you're able to, on a molecular level, kind of restart that process or jump start it or boost it.

[Max Jodeberg]

Aging is an interesting one. You know, this is a really nascent area of research where people are just starting to work out what are some of the factors that reverse the age of cells. Are these things called Yamanaka factors?

[Gary O'Reilly]

Yes.

[Max Jodeberg]

And there's even potential that people are finding of creating molecules that stabilize particular protein. Yamanaka factors are proteins, they're transcription factors that read DNA can stabilize these things. Maybe that is what reverses some of the age of cells. This is super nascent.

[Neil DeGrasse Tyson]

So what is the connection between wanting to modify a genome and your ability to fold proteins to interact with our physiology? I ask that because I'm reminded there was a scene in the film Gattaca where they didn't manipulate your genome, but they selected your pre existing genome for certain properties. And there's a person giving a piano recital and it was very rich sound. I mean, it was beautiful. And then the camera came around to the front and the person had 12 fingers.

[Chuck Nice]

Oh, that's right.

[Neil DeGrasse Tyson]

And bread for that.

[Chuck Nice]

Yes.

[Neil DeGrasse Tyson]

Right. You get two extra notes for every.

[Chuck Nice]

For everything.

[Max Jodeberg]

Right.

[Neil DeGrasse Tyson]

For everything going on.

[Chuck Nice]

She could only play the stuff like nobody could play with.

[Neil DeGrasse Tyson]

Nobody could play with you.

[Chuck Nice]

Nobody could play with you.

[Neil DeGrasse Tyson]

So this would be modifying not to go into space necessarily. Yes, but just to sort of enrich the diversity of the human species.

[Max Jodeberg]

We're not doing genetic modification.

[Neil DeGrasse Tyson]

So. He says he's English.

[Max Jodeberg]

You must trust him to be honest.

[Chuck Nice]

Yes.

[Neil DeGrasse Tyson]

Thank you.

[Gary O'Reilly]

Thank you.

[Chuck Nice]

Well done.

[Neil DeGrasse Tyson]

Well played. But can you. Is it the same thing?

[Max Jodeberg]

Some particular types of drugs are, you know, things that would manipulate your genome. That's how people start to target some diseases. This is not the class of drugs we're working on. When we think about the big ambition of solving all disease, maybe this is something that we need to be doing over time as we wanna really crack the whole spectrum of disease.

[Gary O'Reilly]

Is it even possible to consider that without considering the whole area itself as it all bleeds in together at some point?

[Max Jodeberg]

Yeah, I mean, we need to understand the genome and all the effect. How changing a particular base model pair on your DNA is going to change what proteins are expressed or in what abundance and how that all the knock on effect on the pathways. You really want this basically, this virtual cell to be able to manipulate this cell on a computer to do experiments there.

[Neil DeGrasse Tyson]

Here's what I want you to do.

[Chuck Nice]

It's like your cell template that you're talking about prioritizing.

[Neil DeGrasse Tyson]

And I'm not asking much because it already happens in the animal kingdom. For so long, decades, even centuries, we imagined ourselves at the top of some evolutionary triangle apex without any arrogance whatsoever. Yeah. And all right, yet a newt can regenerate a limb and we can't. And so it seems to. And they're vertebrates. So it seems to me there ought to be some way to extract from animals that do things that we could benefit from and then make that a priority. So people, especially veterans who've lost limbs.

[Chuck Nice]

In conflict or even geckos with their sticky hands. Like maybe I could be Spider man one day.

[Gary O'Reilly]

So organ.

[Neil DeGrasse Tyson]

Let's prioritize that, Chuck.

[Gary O'Reilly]

We'll become superheroes.

[Neil DeGrasse Tyson]

So the regeneration of limbs, that's got to be a protein thing going on in there, isn't it?

[Max Jodeberg]

Yeah. I mean, all of our mechanisms are protein. Same for nukes as well. So there is some mechanism there. I don't know what it is.

[Chuck Nice]

Okay, yeah, gotcha.

[Neil DeGrasse Tyson]

But that would be a mechanism to emulate if you could.

[Chuck Nice]

If you could. Yeah.

[Neil DeGrasse Tyson]

And then install it into our own physiology.

[Max Jodeberg]

It's a big if.

[Chuck Nice]

Yeah, that's a lot. How about this? Would you be able to look at drugs that are already here and there are some drugs that are just not well tolerated and you'd be able to reconfigure them in such a way that you get the benefit of the drug without the side effects.

[Max Jodeberg]

Yeah, exactly. So you often have these first generation of drugs that do something, but they have these side effects. Then there's a big opportunity to understand better how these drugs work. Things like Alpha 3. Things like our models that understand toxicity of drugs can then allow us to potentially modify these to become better drugs and have less side effects, less toxic effects.

[Chuck Nice]

Cool.

[Gary O'Reilly]

Wow. That's going back through the medical catalog. Reanalyzing. Which is exactly what an AI would be perfect for, right?

[Chuck Nice]

Exactly.

[Neil DeGrasse Tyson]

Yeah.

[Chuck Nice]

Yeah. You guys are gonna make a lot of money, man. I don't know how I get.

[Gary O'Reilly]

I've seen dollar signs.

[Chuck Nice]

I'm here to get a piece of this company. You guys are gonna make. I mean, I can't even imagine the amount. The gobs and gobs of money. More money than cells in my body. This is amazing.

[Neil DeGrasse Tyson]

We're in the doorstep of quantum computing. And I know what impact that would have in my field. In your field, would it make your entire life's work look like it was done on an abacus?

[Max Jodeberg]

Yeah, I mean, this is going to change things, I think. Open question, how this changes machine learning, like what can AI do with quantum computing? But for chemistry, even near term, there are some real applications of quantum computers for understanding the properties of small molecule drugs. Because actually some of the things that people do do today with quantum computers is simulate these small chemical systems. Like we actually, even, even in the company, we have a quantum simulation team that are, you know, not using quantum computers, but simulating the quantum effects of molecules. Now if you had a quantum computer that could work on that scale, you could use that instead.

[Chuck Nice]

So, wow.

[Neil DeGrasse Tyson]

I think of so many needs on the frontier of chemistry in modern society. One of them is, you know, what do we do with all the plastic that's in our environment that's still there in the ocean? Is there some life form you can create that'll digest the plastic and turn it back into its original molecules? Are proteins something that could be applied there? If not in your world, then you're describing an ability more than you're describing a specific solution to a problem. You're empowering the chemist in ways never previously imagined.

[Max Jodeberg]

Yes. So you can use the capability of alphafold to understand, you know, understanding structure of proteins. People are using this outside of drug. Drug design.

[Neil DeGrasse Tyson]

Exactly, exactly.

[Max Jodeberg]

People are using this, for example, to create bacteria that have enzymes that could potentially digest plastics like you're talking about. You could think about this for engineering, you know, more resilient types of crops, these sort of things.

[Neil DeGrasse Tyson]

Yeah.

[Chuck Nice]

So just like AI, this is a platform upon which you can rest the technology of any field.

[Max Jodeberg]

So, yeah, that's the amazing thing about the protein folding problem. Once you start to solve that, you unlock so many new things for a whole broad spectrum of science. Right.

[Gary O'Reilly]

There's a lot of downstream benefits, it would seem.

[Neil DeGrasse Tyson]

Okay, last thing.

[Chuck Nice]

Here's the last thing. How do I get a piece of this company?

[Neil DeGrasse Tyson]

Chuck has got dollar talent.

[Chuck Nice]

How do I get a piece of this company?

[Neil DeGrasse Tyson]

Last thing, last thing. What is the worst possible outcome of your work?

[Chuck Nice]

Ooh, what a question.

[Neil DeGrasse Tyson]

What guardrails are necessary as we go forward? Because any new technology with awesome power comes awesome responsibility. Yeah.

[Max Jodeberg]

I mean, I think you have this with AI, you have this creating new biology or chemicals. You just need to think about how to use this responsibly. Like what you're putting out into the world openly versus what you close off for many safety reasons. So I think there's, there's a lot of things to consider there. Yeah.

[Neil DeGrasse Tyson]

Cause famously in one of the Jurassic park films, they withheld lysine amino acid from one of the dinosaurs in case it escaped. It would die because it would need the lysine for its survival. And that was a kind of an insurance plan that put in. But life always finds a way.

[Chuck Nice]

There you go.

[Neil DeGrasse Tyson]

Anyway, Maxwell Jadeberg.

[Gary O'Reilly]

Yeah.

[Neil DeGrasse Tyson]

Thank you for joining us on StarTalk. We're gonna be watching your company and Chuck wants a piece of it.

[Chuck Nice]

Yes.

[Neil DeGrasse Tyson]

I don't know what that means, but anyhow, I'm delighted to just be able to look through your lens at the birth of an entire frontier in human physiology. I mean, what a time this is.

[Max Jodeberg]

No, thank you so much. Been super, super fun to talk.

[Gary O'Reilly]

Yes, thank you.

[Neil DeGrasse Tyson]

Excellent, excellent. All right, I think we're done here. There's been another installment of StarTalk Special Edition talking about AI human physiology and the future of drugs. Oh, yeah. Gary, good to have you. Always pleasure, Neil.

[Chuck Nice]

All right, Chuck, always a pleasure.

[Neil DeGrasse Tyson]

As always, this has been startalk. Neil DeGrasse Tyson, your personal astrophysicist. Keep looking up.

[Max Jodeberg]

At Capella University.

[Chuck Nice]

Learning online doesn't mean learning alone.

[Max Jodeberg]

You'll get dedicated support from people who care about your success. A different future is closer than you think with Capella University.

[Chuck Nice]

Learn more at Capella.

[Max Jodeberg]

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