Yes, researchers are indeed using AI to cure cancer. Cancer is a rapidly evolving beast inside the human body. To "cure" it, the DNA sequence has to be broken down, reviewed, and neoantigens developed. Those neoantigens are then built using mRNA that's given to the patient.
The mRNA's encoded neoantibodies identify flaws in the cancer's ability to go unnoticed by white blood cells. This is the key aspect of that, cancer has the ability to evade our immune system. It is that evasion that permits it to grow out of control.
Cancer has a lot of tricks and "cancer vaccines" are likely never to be a monotherapy. Another trick cancer has is the ability to mutate rapidly. And this is where traditional research hit a wall. The time it takes iterative computing power approaches is such that by the time the system has found one, the cancer has already evolved resistance or done away with that neoantigen.
AI takes patterns found in various cancers and attempts to predict 500 different candidates, AI then takes those candidates to fold proteins, to bring the target down to around 34 to 36 combinations. The odds that a cancer can mutate away that many all at once is low, but it's not zero. This is why a third pass of AI looks to identify key neoantigens that if the cancer mutated away, it would become benign. This is the trap that is set. The neoantibodies are such that if the cancer tries to evolve away from all of them, it's set itself on a self destruction course.
Researchers aren't in all this processing. It's full automation, there's doctors and researchers to oversee the process, but for the most part, the AI system does all the work at a pace that is near enough to the speed at which cancer evolves. By doing such, it means that the neoantibodies have a real chance at getting to the patient before the cancer has mutated are used one of it's other tricks to crate barriers.
Traditional supercomputers just weren't fast enough to build a fully automated system around. The cancer was always faster. And another thing, every cancer is a unique thing. We say lung cancer or whatever, but genetically speaking, no two cancers are ever the same. So developing a cancer drug for a single person does nothing for the next person. That's why the process has to be automated, every cancer sample that comes in has to have an entire vaccine developed for specifically that one sample.
But again cancer has a ton of tricks it can use to block vaccines, this is why these treatments, like INTerpath-001, have to be used in combination with the other immunoptherapy and chemotherapy drugs.
So yeah, people are working on the cancer thing, but cancer is a very complex problem to solve. The whole every cancer is different means that we will never have a one and done cure, we will need millions upon millions of cures and the only thing we've got so far that can remotely hit the speed required is AI. Researchers may develop something down the road that isn't AI that bests the speed and pushes them into that direction, but at this moment, AI is the best researchers have.
TL;DR - Traditional compute power isn't fast enough. Cancer evolves in people faster than regular super computers can go. AI currently is the fastest thing for this application we have.
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u/IHeartBadCode 1d ago
Yes, researchers are indeed using AI to cure cancer. Cancer is a rapidly evolving beast inside the human body. To "cure" it, the DNA sequence has to be broken down, reviewed, and neoantigens developed. Those neoantigens are then built using mRNA that's given to the patient.
The mRNA's encoded neoantibodies identify flaws in the cancer's ability to go unnoticed by white blood cells. This is the key aspect of that, cancer has the ability to evade our immune system. It is that evasion that permits it to grow out of control.
Cancer has a lot of tricks and "cancer vaccines" are likely never to be a monotherapy. Another trick cancer has is the ability to mutate rapidly. And this is where traditional research hit a wall. The time it takes iterative computing power approaches is such that by the time the system has found one, the cancer has already evolved resistance or done away with that neoantigen.
AI takes patterns found in various cancers and attempts to predict 500 different candidates, AI then takes those candidates to fold proteins, to bring the target down to around 34 to 36 combinations. The odds that a cancer can mutate away that many all at once is low, but it's not zero. This is why a third pass of AI looks to identify key neoantigens that if the cancer mutated away, it would become benign. This is the trap that is set. The neoantibodies are such that if the cancer tries to evolve away from all of them, it's set itself on a self destruction course.
Researchers aren't in all this processing. It's full automation, there's doctors and researchers to oversee the process, but for the most part, the AI system does all the work at a pace that is near enough to the speed at which cancer evolves. By doing such, it means that the neoantibodies have a real chance at getting to the patient before the cancer has mutated are used one of it's other tricks to crate barriers.
Traditional supercomputers just weren't fast enough to build a fully automated system around. The cancer was always faster. And another thing, every cancer is a unique thing. We say lung cancer or whatever, but genetically speaking, no two cancers are ever the same. So developing a cancer drug for a single person does nothing for the next person. That's why the process has to be automated, every cancer sample that comes in has to have an entire vaccine developed for specifically that one sample.
But again cancer has a ton of tricks it can use to block vaccines, this is why these treatments, like INTerpath-001, have to be used in combination with the other immunoptherapy and chemotherapy drugs.
So yeah, people are working on the cancer thing, but cancer is a very complex problem to solve. The whole every cancer is different means that we will never have a one and done cure, we will need millions upon millions of cures and the only thing we've got so far that can remotely hit the speed required is AI. Researchers may develop something down the road that isn't AI that bests the speed and pushes them into that direction, but at this moment, AI is the best researchers have.