Pathos AI has raised $365m in a Series D funding round as it prepares to widen its AI-enabled platform to advance the development of oncology drugs.
This finance boosts the company’s post-money valuation to an estimated $1.6bn.
Go deeper with GlobalData
The proceeds from the round will progress Pathos AI’s clinical-stage pipeline and further develop its AI Foundation Model, specifically designed for oncology.
The company is creating a multimodal foundation model in the field, utilising clinical, imaging and molecular data to refine the selection of clinical assets, study design, discovery of biomarkers and therapeutic innovation.
Pathos AI CEO Iker Huerga stated: “Pathos was founded to transform drug development by harnessing the full potential of multimodal data and AI.
“With this financing, we’re building one of the most advanced AI engines, designed to accelerate development, deepen clinical insight and ensure the right therapies reach the patients who need them most.”
US Tariffs are shifting - will you react or anticipate?
Don’t let policy changes catch you off guard. Stay proactive with real-time data and expert analysis.
By GlobalDataIn March 2025, Pathos AI announced the first subject dosing in its Phase Ib/IIa clinical trial.
The trial is designed to assess CBP/p300 inhibitor and the company’s first clinical-stage asset in the pipeline, pocenbrodib, both as monotherapy and in conjunction with olaparib, abiraterone acetate or 177Lu-PSMA-617 to treat metastatic castration-resistant prostate cancer (mCRPC).
In a collaborative effort focusing on cancer drug discovery, Pathos AI, AstraZeneca and Tempus entered a multi-year agreement in April 2025.
The partnership is set to develop a large-scale, multimodal deep learning model that could expedite the identification of drug targets and support the creation of new cancer treatments. Tempus stands to gain $200m from data licencing and model development fees as part of this deal.
Pathos AI is focused on expediting innovation in oncology through a new model for drug development.
By integrating multimodal data, AI and deep clinical insights, the company aims to deliver new treatments to patients more quickly.
