Google’s AlphaGenome 2 zooms in on the cellular roots of disease

AI Science Tech Google’s AlphaGenome 2 zooms in on the cellular roots of disease DeepMind’s new DNA model better predicts how mutations affect different cells, potentially opening paths to treatment.

DeepMind’s new DNA model better predicts how mutations affect different cells, potentially opening paths to treatment.

AlphaGenome 2 is the successor to DeepMind’s genome-predicting AI model AlphaGenome, which was released last year . While nearly every cell in the human body carries the same DNA, different types of cells — from heart muscle cells and skin cells to immune cells fighting an infection — switch different genes on and off, and those patterns can change depending on what a cell is doing. As a result, the same genetic variant can have very different effects depending on the type and state of the cell.

The new model is designed to capture those differences, predicting the effects of genetic variants on individual cell types and states. Google said in a blog post published Wednesday that it offers a much finer-grained view than broader models like AlphaGenome, potentially revealing disease-relevant effects in specific cells that might otherwise go unnoticed.

Google DeepMind’s genomics lead Žiga Avsec told The Verge that this specificity is important if you have a goal like figuring out how to treat a particular disease. “When you develop drugs, you’re targeting specific proteins and specific cell types,” he explained, which makes having this kind of granularity vital.

Building a model like AlphaGenome 2 has only recently become possible thanks to new technologies that can capture individual cells and their states at high resolution and create the vast datasets needed to train it, Avsec said. DeepMind is now working to improve its genetics models by generating more data, including for cell states that aren’t represented well today. Avsec said future versions could also potentially be trained on data “across multiple species,” giving the models a broader view of biology. Longer term, he said models like AlphaGenome 2 could feed into efforts to create “ virtual cells ,” digital simulations designed to mimic biological systems.

Although Avsec said he views AlphaGenome 2 as a successor to AlphaGenome, it isn’t replacing it any time soon. He said its more detailed predictions come at a computational cost and are “more expensive” to produce than those of its predecessor, he said. Those demands would have made it impractical to use AlphaGenome 2 to produce the genome-wide Atlas covering “every possible DNA letter change in the human genome” that DeepMind released in September.

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