Sanofi tests AI lab-in-a-loop to speed drug discovery, AdExchanger op-ed says
Bringing a new drug to market costs the pharma industry $2.6 billion on average and takes 12 to 15 years, with only a 10% success rate, according to an AdExchanger op-ed by Ian Colley. Sanofi is developing a lab-in-a-loop that uses AI agents to potentially compress elements of that discovery work from years to weeks. The share of FDA drug approvals addressing rare conditions has climbed from below 30% to above 50% over the past decade or so, the op-ed says, as AI-driven research opens treatments to smaller patient populations. Ultragenyx faced that problem directly: its 2013 launch of Crysvita, the first treatment for X-linked hypophosphatemia, struggled until the company added disease education, free gene testing and payer assistance to find the small population of eligible patients and doctors.
Campaigns built for pharma's rarest treatments must find a few thousand patients and providers scattered across the country. Colley argues that programmatic advertising, built to optimize mass-reach campaigns, needs a different toolset for that kind of precision targeting. Early tests of agentic AI tools have already cut marketing planning and execution cycles for new treatments by as much as 10x, a preview of how AI agents could compress forecasting and scenario planning work well beyond pharma. More than 10,000 rare diseases still have no approved treatment, and Colley frames faster, cheaper commercialization planning as one piece of getting a viable drug to the patients who need it.