DeepMind is using AI to pinpoint the causes of genetic disease

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Now the company says it has fine-tuned that protein model to predict which misspellings found in human DNA are safe to ignore and which are likely to cause disease. The new software, called AlphaMissense, was described today in a report published by the journal Science

As part of its project, DeepMind says, it is publicly releasing tens of millions of these predictions, but the company isn’t letting others directly download the model because of what it characterizes as potential biosecurity risks should the technique be applied to other species.

Although not intended to directly make diagnoses, computer predictions are already used by doctors to help locate the genetic causes of mysterious syndromes. In a blog post, DeepMind said its results are part of an effort to uncover “the root cause of disease” and could lead to “faster diagnosis and developing life-saving treatments.”

The three-year project was led by DeepMind engineers Jun Cheng and Žiga Avsec, and the company said it is publicly releasing predictions for 71 million possible variants. Each is what’s known as a missense mutation—a single DNA letter that, if altered, changes the protein a gene makes.

“The goal here is, you give me a change to a protein, and instead of predicting the protein shape, I tell you: Is this bad for the human that has it?” says Stephen Hsu, a physicist at Michigan State University who works on genetic problems with AI techniques. “Most of these flips, we just have no idea whether they cause sickness.”

Outside experts said DeepMind’s announcement was the latest in a string of flashy demonstrations whose commercial value remains unclear. “DeepMind is being DeepMind,” says Alex Zhavoronkov, founder of Insilico Medicine, an AI company developing drugs. “Amazing on PR and good work on AI.”

Zhavoronkov says the real test of modern artificial intelligence is whether it can lead to new cures, something that still hasn’t happened. But some AI-designed drugs are in testing, and efforts to create useful new proteins are a particularly hot sector, investors say. One company, Generate Biomedicines, just raised $273 million to create antibodies, and a team of former Meta engineers started EvolutionaryScale, which thinks AI can come up with “

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