Designing new medicines is a lengthy and costly process, with many potential candidates failing before reaching patients. This is especially true for biologic medicines, which are complex engineered proteins. AI is now revolutionizing pharmaceutical R&D by significantly speeding up these processes.

Companies like AstraZeneca are integrating AI into their R&D, enabling faster design cycles and increased productivity. AI models computationally generate and prioritize drug candidates, allowing scientists to focus lab resources on the most promising options. This tighter feedback loop enables the pursuit of previously untreatable diseases.

AI's impact extends to discovering entirely new drug classes capable of targeting multiple pathways or delivering therapies to specific cells. McKinsey estimates generative AI could cut drug discovery timelines by up to 50%. AstraZeneca is building a "lab of the future" in Kendall Square, Massachusetts, combining AI and robotic automation for a continuous discovery system. The ultimate goal is "de novo" design, where AI generates entirely new protein sequences for drugs from scratch, with safety prediction being a critical challenge being addressed through virtual clinical trials.