The agreement means that tense will receive $200 million in licensing and model development fees, giving all three parties access to the resulting model including underlying data and data analytics. The aim is to use AI to analyze large amounts of biological and clinical data, identify new drug targets and support the development of precision medicine for cancer patients. The collaboration builds on an existing partnership between AstraZeneca and Tempus, which began in 2021 and has so far focused on non-small cell lung cancer.
Tempus contributes a comprehensive database of identified oncological data, while Pathos AI brings expertise in biological simulations to explore drug interactions and disease mechanisms.
- Generative AI and the emergence of large multimodal models is the final catalyst needed to usher in precision medicine in oncology at scale, comments Tempus founder and CEO Eric Lefkofsky. Tempus has spent the last decade investing billions of dollars into collecting the necessary data needed for a foundation model of this kind to take shape. We look forward to working with AstraZeneca and Pathos to apply AI-enabled solutions to advance therapies in an effort to help patients live longer and healthier lives.
Part of a larger initiative
This is not the first AI collaboration AstraZeneca has signed. The company began last year with a collaboration with Impeller, which aims to use AI-powered simulations to explore mechanisms behind drug resistance in blood cancers. Unlike traditional lab-based methods, the models can generate millions of simulations to analyze complex biological processes in a fraction of the time it normally takes.
- Cancer drug discovery and clinical development are being transformed by the ability to analyze vast amounts of rich data using artificial intelligence, says Jorge Reis-Filho, Head of Oncology AI at AstraZeneca on the latest deal with Tempus and Pathos. We are excited to collaborate with Tempus and Pathos to advance our data and AI-driven R&D strategy through the development of a multimodal oncology foundation model that we believe will accelerate and increase the probability of clinical success across our diverse pipeline.
