Owkin and AstraZeneca have entered a three-year licensing agreement centered on K Pro, Owkin’s AI Scientist platform designed to support pharmaceutical research, competitive intelligence, and drug development decision-making. Under the agreement, Owkin will develop AI agents for AstraZeneca teams that will operate through the K Pro platform while integrating with the pharmaceutical company’s existing IT systems and research workflows.
The AI agents are intended to assist AstraZeneca in analyzing and forecasting competitive intelligence related to pharmaceutical targets, clinical trials, and drug assets. The platform is built on Owkin’s multimodal patient data network and AI infrastructure, which are designed to support complex pharmaceutical research activities and strategic planning.
“These agents will help AstraZeneca's decision-making teams access timely, data-rich insights for complex competitive intelligence questions, reducing reliance on manual analysis within established governance, security and enterprise standards,” said Jonas Beal, head of product at Owkin.
The agreement expands an existing collaboration between the two companies focused on oncology-related AI applications. Previously, Owkin and AstraZeneca worked together on an AI-powered gBRCA pre-screening tool intended to identify breast cancer patients who may benefit from targeted therapies. Findings from that project were presented at the European Society for Medical Oncology Congress.
Beal emphasized the importance of using multimodal patient datasets to improve pharmaceutical research outcomes. “Patients cannot be summed up in a few data points – you need deep multimodal patient data to capture their heterogeneity, ideally from recent standard-of-care cohorts that reflect how patients are treated today,” he said.
He added that large language models alone are not sufficient for analyzing raw healthcare data without extensive preparation and modeling. “However, LLMs can't properly analyze this kind of raw data. It needs to be made AI-ready and quantified through expert AI tools and models,” Beal said.
According to Beal, AI-driven approaches can significantly reduce timelines for research activities. “For example, target prioritization, biomarker identification, cohort characterization – amongst others – can be achieved in days rather than months,” he said.
The partnership reflects broader activity across the pharmaceutical industry, where companies are increasingly adopting agentic AI systems to support research and development. “We believe that agentic AI is the future of pharmaceutical R&D,” Beal said. “This will bring increasing productivity and new biology to the full pharmaceutical workflow.”
Click here for the original news story.
