Artificial intelligence has not yet delivered the industry\u2019s most anticipated breakthrough\u2014consistently discovering new molecules that become major medicines\u2014but it is already making a measurable impact in drug development\u2019s day-to-day workload. At the JP Morgan Healthcare Conference, executives from seven large drugmakers and six biotech companies said AI is accelerating operational processes such as selecting clinical trial sites, finding participants, and drafting regulatory documentation.<\/p>\n\n\n\n
Those improvements matter in an industry where bringing a new drug to market can take around a decade and cost $2 billion. Companies including Eli Lilly, which has partnered with Nvidia, are betting AI will eventually improve research productivity and increase the probability of drug success. For now, however, the biggest gains are coming from streamlining the \u201cmessy middle\u201d of development\u2014administrative and execution-heavy tasks that can quietly delay programs by weeks or months.<\/p>\n\n\n\n
A major challenge is the scale and complexity of regulatory submissions. Firms such as AstraZeneca, Roche, and Pfizer must track and reconcile thousands of pages of clinical, safety, and manufacturing documentation across multiple regions and standards. AstraZeneca CFO Aradhana Sarin noted that compiling and cross-checking these materials is expensive and often requires outside contractors, making it a prime target for automation.<\/p>\n\n\n\n
Consultants and investors see momentum building around agentic AI\u2014tools that operate with minimal human intervention. McKinsey has estimated that agentic AI could lift clinical development productivity by roughly 35% to 45% over the next five years. Andreessen Horowitz investor Jorge Conde is backing solutions like Alleviate Health to address clinical trial enrollment, which he describes as a \u201cleaky funnel\u201d where participants drop out before completing screening and scheduling.<\/p>\n\n\n\n
Pharma leaders are already sharing tangible examples. Novartis used AI during planning for a 14,000-patient cardiovascular outcomes study for Leqvio, shrinking a four- to six-week site-selection process into a two-hour meeting. GSK said its digital and AI tools helped reduce trial timelines and saved about 8 million pounds in late-stage studies for its asthma drug Exdensur.<\/p>\n\n\n\n
While the \u201cAI drug\u201d remains the headline goal, companies increasingly view today\u2019s operational wins as the clearest path to near-term returns\u2014and a foundation for the next generation of innovation.<\/p>\n\n\n\n