economist Many life sciences companies are reportedly betting big on AI to help with drug development. Why? If AI can increase the chances of new molecules becoming successful drugs, the cost of drug development will go down.
AI-designed molecules show 80-90% success rates in early-stage safety trials, while the historical average is only 40-65%. It will take years to become clear whether success rates also increase in later-stage trials. But even if they don’t, one model suggests that early-stage improvements alone could increase success rates across the entire pipeline from 5-10% to 9-18%.
Tech companies are also growing in life sciences:
A new generation of AI-native biotech startups is emerging, especially in the US and China. Pharma companies are increasingly forming tie-ups with AI-biotech firms as well as technology giants including Amazon, Google, Microsoft and Nvidia. And those big tech companies have their own ambitions in the health sector. Isomorphic Labs, a spin-out of Google DeepMind, is trying to design entirely new therapeutic molecules from scratch inside computers. Nvidia also has a generative-AI platform for drug discovery. Both the companies are signing an agreement to provide 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:
The US Food and Drug Administration and the European Medicines Agency are starting to use AI to screen the reams of data they receive. As the number of drug candidates increases, faster regulatory reviews will be needed to avoid deadlock.
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