DeepMind “stunned” scientists with their neural network-based protein folding results. In computational biology, protein folding is the task to predict the three-dimensional structure of a protein given its sequence. Knowing how a protein folds is important for medical drug development, but for larger proteins this structure is difficult to predict. Robert Langreth for Bloomberg:
Artificial intelligence is a chic catchphrase in health care, often trotted out as a cure-all for whatever ails the industry. It has been held up as a potential solution to fix cumbersome electronic medical records, speed up diagnosis and make surgery more precise. DeepMind’s victory points to a possible practical application for the technology in one of the most expensive and failure-prone parts of the pharmaceutical business.
Machine learning-based drug discovery is becoming a big deal in Silicon Valley, with medical AI startups like Recursion Pharmaceuticals, Insitro, BenevolentAI and others raising over $1 billion in 2018 alone. Big tech labs, like Google’s and Facebook’s, have also started published papers on protein folding recently. All this work is going toward simulating the effects of drugs without having to test them clinically:
An aerospace company “won’t build and fly a plane without building it on the computer first and simulating it under many conditions,” said Colin Hill of GNS Healthcare, a startup using AI to model disease, whose investors include Amgen Inc.
In the future, drugmakers won’t begin clinical trials without a virtual dry run, Hill said.
Although this practical AI application is still mostly in the research phase, these recent articles are a good indication that we’ll probably start seeing it being productized (or, in this case, used to develop medicine) in the coming years: