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Pathos AI Secures $237M in Series E Financing to Scale Agentic AI Drug Development Platform and Advance Oncology Pipeline

Insider Brief

  • Pathos AI, a New York-based clinical-stage AI and technology company developing its own drugs, has closed a $237 million Series E at a post-money valuation of about $3 billion, led by Bristol Myers Squibb with participation from existing investors.
  • The company’s proprietary AI platform, Foundry, uses thousands of specialized AI agents to synthesize clinical, genomic and competitive data in real time and identify the best next decision for each drug program, helping Pathos rapidly expand its oncology pipeline to four active clinical assets.
  • CEO Iker Huerga said the platform aims to systematically improve the probability of success in drug development, with the funding set to scale Foundry and advance programs including JSKN016, a first-in-class TROP2/HER3 bispecific antibody-drug conjugate, toward registrational studies, alongside AZD4241, partnered with AstraZeneca.

PRESS RELEASE — Pathos AI, Inc., a clinical-stage AI and technology company advancing its own therapeutic pipeline of drugs, announced the closing of a $237 million Series E financing round at a post-money valuation of approximately $3 billion. The financing was led by Bristol Myers Squibb (NYSE: BMY), alongside participation from existing investors.

The capital raise reflects significant operational momentum driven by Pathos’s proprietary AI platform, Foundry. Over the past several months, the company has leveraged Foundry to aggressively expand its clinical-stage oncology portfolio through a series of rapid strategic transactions, bringing its pipeline to four active clinical assets.

Proceeds from the financing will be used to further scale the Foundry platform’s capabilities and accelerate the clinical development of Pathos’s AI-steered portfolio. A key priority for the funding will be advancing JSKN016, a first-in-class TROP2/HER3 bispecific antibody-drug conjugate (ADC) toward registrational studies. Additionally, capital will drive the clinical advancement of pocenbrodib in mCRPC and RRMM; AZD4241, a novel ER PROTAC partnered with AstraZeneca, and DO-2, a next-generation MET kinase inhibitor.

“We are building a platform to systematically improve the probability of success in drug development,” said Iker Huerga, CEO of Pathos. “Foundry has fundamentally accelerated our ability to identify highly promising clinical assets and integrate them into our pipeline. This capital allows us to rapidly scale our AI engine while actively steering our current programs toward key clinical milestones, ensuring we deliver the right therapies to the right patient populations.”

Pathos’s clinical velocity is powered by Foundry, which operates via thousands of specialized AI agents that aggregate the totality of information for a drug program in real time. By continuously synthesizing clinical data, genomics, biological specimen data, and the ever-changing competitive landscape, Foundry identifies the optimal next decision for a program. This continuous intelligence allows Pathos to pinpoint precise biological sub-populations, steer clinical trial pivots, and eliminate high-risk development paths early in a drug’s lifecycle.

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.

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James Dargan
About the author
James Dargan

James Dargan is a writer and researcher at The AI Insider. His focus is on the AI startup ecosystem and he writes articles on the space that have a tone accessible to the average reader.

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