Pathos AI Announces Strategic Collaborations with Bristol Myers Squibb and Tempus AI to Advance AI-Driven Drug Development Beginning with Alzheimer’s Disease and Other Neurological Conditions

Pathos commits $55 million over five years to license neurological patient data, while Bristol Myers Squibb leads its Series E financing.

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• Tempus to build a de-identified dataset from hundreds of thousands of patients with neurological conditions; Pathos to license the dataset under a five-year, $55 million agreement
• Pathos’s AI expertise and agentic AI platform, Foundry, combined with Bristol Myers Squibb’s (BMS) neuroscience drug development expertise to be applied to understanding disease progression and advancing new therapies
• BMS leads Pathos’s Series E financing and gains non-exclusive strategic access to Pathos’s AI platform, Pathos Foundry, across its broader portfolio, along with three-year exclusive rights to support its neuroscience development programs

NEW YORK--(BUSINESS WIRE)-- Pathos AI, a clinical-stage AI and technology company advancing its own therapeutic pipeline, today announced multi-year strategic collaborations with Bristol Myers Squibb (NYSE: BMY, “BMS”) and Tempus AI, Inc. (NASDAQ: TEM, “Tempus”) to build a specialized, curated dataset and agentic AI capabilities for Alzheimer’s disease and other neurological conditions. BMS also leads Pathos’s Series E financing and gains access to Pathos Foundry across its broader R&D portfolio.

Tempus will apply the infrastructure and expertise it has built in oncology to create a comprehensive, de-identified, longitudinal dataset from hundreds of thousands of patients with neurological conditions, designed to track outcomes over time and accelerate biological insight. Pathos will license the data from Tempus under a five-year, $55 million agreement.

Pathos will apply its AI platform, Pathos Foundry, to interrogate the dataset at scale, generate and test hypotheses on disease biology, and inform the design of more targeted, adaptive clinical trials. Pathos built and validated this approach in oncology, where it guides decisions across the company’s clinical-stage pipeline, including adapting trial design in real time to improve its projected probability of success.

The collaboration builds on BMS's broader strategy to combine advanced AI with deep scientific and disease-area expertise to make faster, higher-confidence decisions that drive innovation for patients. BMS is helping expand the application of Pathos Foundry into neuroscience, securing three-year exclusive rights in an area where the company brings deep research, clinical-development expertise and a growing portfolio of programs in Alzheimer’s disease and other neurological conditions. Through multi-year access to the platform across its broader portfolio and the specialized dataset developed through the definitive agreements, BMS aims to generate deeper insights into disease progression, identify patients most likely to benefit from potential therapies and design more precise clinical trials.

“Neurological diseases demand more than any one company can bring on its own: the best longitudinal data, AI that can reason over it at scale, and the drug development expertise to turn insight into medicines,” said Iker Huerga, CEO of Pathos AI. “Intelligence alone does not bring a therapy to market. These collaborations bring all three together. We are thrilled to deepen our work with Tempus and proud to have BMS leading our Series E as we build a self-learning drug development system designed to adapt clinical trials and improve the likelihood of success.”

“AI has the greatest potential when it is grounded in high-quality data and applied by scientists with deep understanding of diseases and drug development,” said Simon Davies, SVP, Head of Data and Quantitative Sciences, Bristol Myers Squibb. “Our investment in Pathos reflects our commitment to applying advanced AI and data science across research and development to accelerate innovation for patients. By combining AI-driven insights with our neuroscience expertise, we hope to deepen our understanding of disease progression, improve clinical-trial design and ultimately advance new treatment options. Collaborating with Pathos and Tempus allows us to interrogate Alzheimer’s and other neurological diseases at scale, strengthening our pipeline and advancing precision medicine for patients in need.”

“Making meaningful progress against a disease as devastating as Alzheimer’s requires unprecedented data scale and computing power,” said Eric Lefkofsky, Founder and CEO of Tempus. “These collaborations unite BMS’s deep expertise, Pathos’s drug development agentic AI and Tempus’ data infrastructure. Together, we have a unique opportunity to uncover novel insights and accelerate much-needed treatments for Alzheimer’s patients.”

About Pathos AI

Pathos AI is an AI and technology company developing drugs. The company redesigns drug development from first principles: identifying clinical assets, making portfolio decisions with continuously updated probability-of-success calculations, and guiding clinical trials with AI-native monitoring. Pathos’s pipeline includes clinical-stage programs in metastatic castration-resistant prostate cancer, multiple myeloma, MET-altered non-small-cell lung cancer, ER+/HER2‐ breast cancer, and TROP2/HER3-expressing solid tumors. The company is based in New York City. For more information, visit pathos.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20261023830134/en/

For inquiries, please reach out to press@pathos.com

Source: Pathos AI

Key Terms

de-identified technical

Data labeled as de-identified has had names and other direct personal details removed or masked so individual people cannot be readily recognized; think of it like blurring faces and removing name tags from a photo. For investors, de-identification matters because it reduces legal and privacy risk, can change how valuable or usable the data is for research or product development, and affects regulatory compliance and potential liabilities.

longitudinal dataset technical

A longitudinal dataset is a collection of observations that repeatedly measure the same subjects, entities, or units (for example, people, companies, or securities) at multiple points in time. It records how variables change within those same subjects across successive periods, enabling analysis of trends, timing of events, and relationships that unfold over time; this contrasts with a cross-sectional dataset, which captures many subjects at a single point. Longitudinal data can be organized as panel data (fixed subjects tracked over regular intervals) or as cohort follow-ups (subjects tracked from a common starting event), and it requires methods to handle gaps when subjects miss some measurement times or drop out entirely.

agentic ai technical

Agentic AI refers to computer systems that can make their own decisions and take actions without needing someone to tell them what to do each time. It's like giving a robot a degree of independence to solve problems or achieve goals on its own, which matters because it could change how we work and interact with technology in everyday life.