The Economist reports that many life science companies are betting big on AI to help with drug development. Why? If AI can increase their likelihood new molecules become successful drugs, the cost of drug development will fall.
AI-designed molecules show an 80-90% success rate in early-stage safety trials, compared with a historical average of just 40-65%. It will be years before it becomes clear whether success rates rise in later-stage trials, too. But even if they do not, one model suggests that early-stage improvements alone could increase the success rate across the entire pipeline from 5-10% to 9-18%.
Tech companies may be increasing involved in life science as well:
A new generation of AI-native biotech startups—particularly in America and China—is emerging. Pharma companies are increasingly forming alliances with AI-biotech firms, as well as with technology giants including Amazon, Google, Microsoft and Nvidia. And those big tech firms have their own ambitions in health. Isomorphic Labs, a spin-out from Google DeepMind, is trying to design entirely new therapeutic molecules from scratch inside a computer. Nvidia, too, has a generative-AI platform for drug discovery. Both firms are signing deals to offer design services to pharma companies. And in October Nvidia teamed up with Eli Lilly, the world’s most valuable drugmaker, to build the pharma industry’s most powerful supercomputer.
Regulators are also using AI as well:
America’s Food and Drug Administration and the European Medicines Agency are themselves starting to use AI to screen the mountains of data they receive. As the number of drug candidates rises, faster regulatory reviews will be needed to avoid a logjam.
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