A team of scientists at the University of Toronto have successfully implemented artificial intelligence (AI) tools to speed up the process of discovering new possible cancer treatments, from years to just a month.

Toronto

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Rise of AI

A team of scientists at the University of Toronto is pioneering a faster approach to drug development by utilizing artificial intelligence (AI). This innovative application of technology shortens the drug discovery process from years to just a month, presenting new possibilities for cancer treatment. Typically, drug development is time-consuming and costly, involving meticulous research, and the identification of protein structures through methods like X-ray crystallography. However, AI is revolutionizing this field by efficiently predicting protein structures and helping design effective drug molecules.

Dr. Alon Aspuduguzic and his team at the University of Toronto Acceleration Consortium have demonstrated the prowess of AI in expediting drug discovery. Last year, using AI tools, they were able to create a new compound for treating a specific type of liver cancer much quicker than traditional methods. They employed AI to identify a protein target, determine its structure using Google's DeepMind tool AlphaFold, and designed a drug that binds to it. This process was further aided by automated lab technology to refine reactions swiftly.

Although AI poses potential risks, such as misuse in developing harmful substances, the University of Toronto team emphasizes the focus on safety and the positive impact on scientific productivity. They view AI as a tool to enhance human capability, enabling scientists to conduct more parallel experiments and address pressing societal issues. The ultimate goal is to accelerate scientific discovery while ensuring the ethical and safe use of AI technology.



Breakthroughs in AI helping to design life-saving drugs faster

Developing new medications has historically been a slow process, requiring years of trial-and-error research, millions of dollars, and often luck. Finding drugs is like finding needles in haystacks. Just to get an X-ray structure of a protein can take up to a year. Knowing a protein structure is key. It lets scientists design drug molecules that bind to those proteins and change their function. Until recently, most human protein structures were unknown. If you don't know how the protein looks like, how do I do anything? There's even Nobel Prizes given to people that found the X-ray structure of important proteins. And without a protein structure, scientists don't know what to create. It would be like trying to make a puzzle piece without knowing what the other piece even looks like. But Dr. Alon Aspuduguzic and his team at the University of Toronto Acceleration Consortium say AI can speed everything up. Last year, using three separate applications of AI, Aspuduguzic's lab created a new compound that could help treat a type of liver cancer in a fraction of the time it takes for most drug discoveries. AI is good about finding patterns that the humans don't find as obvious. We use all the data to do less trials, less computational attempts at finding the solution. First, they used AI to find a target protein that might affect the cancer. A protein in liver cancer that has not been targeted before. But we also wanted this protein to not have a three-dimensional structure known. So the structure wasn't known. To figure out the protein structure, they used a Nobel Prize-winning AI system called AlphaFold from Google DeepMind, which made the breakthrough achievement of predicting every human protein structure. AlphaFold, can you tell me how this protein looks like? And AlphaFold predicted the protein. Finally, they used another AI tool to design a drug that binds to that predicted protein. Combined with automated robots, they could fine-tune that design faster than humans can, with what they call a self-driving lab. This is a robot that allows us to actually carry out liquid dispensing, powder dispensing, etc. Combined with that robot, we can actually make our reactions happen here. So you're not standing over a little flame holding a beaker. AI helped us go 200 times faster to find the best molecule. Every time we made a molecule, AI found hints. It's like a sleuth, right? And told us, this is the next best molecule to make. All in, it took the lab just 30 days to find a potential drug compound for liver cancer, in what normally takes a year or two. But is there a risk that somebody could use the power of AI, this data and the prediction capabilities, to do something dangerous, to develop a superbug or something like that? It's very hard when you develop a fundamental technology not to worry about the potential bad aspects. Like if somebody wanted to poison somebody, they would just give them some poison. Right. AI-generated poison might not be as useful as people think. Definitely in general, especially in chemical safety, we do care a lot about how to make sure everything that we do is good. Is there a risk that the technology replaces humans in the process, or does the role of the humans just change? So think about this as a productivity tool for scientists. If the scientists can be thinking higher-level things, can be organizing experiments that are way more parallel, we can actually accelerate scientific discovery. What we want the scientists to do is to be more proactive to solve the problems that are pressing for society nowadays.

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Rise of AI