Can AI really cut drug discovery timelines by 50%
pharma giant astrazeneca is using ai to design biologics and shorten r&d cycles by years. the tech is making previously 'undruggable' targets treatable.
astrazeneca is applying machine learning to optimize the design of biologics, moving from a decade-long development process to a computational build-measure-learn loop. the technology allows researchers to filter through vast molecular combinations computationally, focusing lab resources only on candidates with the highest predicted success rates for potency and stability. this capability enables the creation of complex, multi-specific medicines that can hit multiple disease targets simultaneously. mckinsey estimates generative ai could cut discovery timelines by 50%, though efficacy depends on high-quality proprietary data. the industry is shifting toward ai-first infrastructure to 'drug the undruggable'.