Pharma Turns to AI to Cut $1 Billion Drug-Development Risk

7 articles · Updated · Bloomberg · May 18

Drugmakers are increasingly testing AI to speed discovery and make development more predictable, targeting one of the industry's biggest cost and failure bottlenecks.
About 10 years and more than $1 billion are typically needed to move a medicine through clinical trials, and roughly 90% of candidates never reach approval.
That attrition reflects a traditional process in which researchers form a hypothesis, run repeated tests to find a useful compound, then keep refining it for potency, safety and durability.
The industry's AI push aims to shorten that trial-and-error cycle, potentially reshaping how new treatments are identified and advanced toward FDA review.

With the FDA now fast-tracking drugs, is AI pushing medicine into a new era of innovation or one of unforeseen risk?

AI is acing early drug safety trials, but can it solve the bigger challenge of making drugs that actually work?

AI promises to slash drug development costs. Will patients see lower prices, or will profits just soar for big pharma?