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Valinor Raises $13M to Increase Clinical Trial Success Rates with Proprietary ML Models

Insider Brief

  • Valinor raised $13 million in seed funding led by CRV and others to expand its AI platform for predicting patient response in clinical trials.
  • The company uses multimodal machine learning trained on matched multi-omic and clinical outcome data to identify likely responders, reduce trial risk, and uncover new biological insights.
  • The funding will support growth of Valinor’s proprietary datasets and hiring of additional machine learning talent to accelerate drug development partnerships.

PRESS RELEASE — Valinor, a pioneering AI company leveraging advanced machine learning models to increase the probability of clinical trial success by deeply understanding patient response, announced $13 million in funding. The seed funding was led by CRV, Harpoon Ventures, Amino Collective, and Pelion Venture Partners. Other participants include numerous leading angel investors and operators such as Charlie Songhurst, Surya Midha (co-founder of Mercor), Axel Ericsson, and Kyle Harrison.

“Our models are built to surface meaningful features that underlie patient response. We believe this approach will empower our pharmaceutical partners to improve clinical trial success rates, cut R&D costs and, most importantly, speed the delivery of life-saving medicines to patients,” said Joshua Pacini, Founder and Chief Executive Officer of Valinor. “With this funding, we are accelerating the expansion of our proprietary matched omics and clinical outcome datasets and advancing our AI models that allow our pharma partners to make smarter, data-driven decisions in drug development.”

Valinor’s models are trained on matched datasets of patient-derived multi-omic samples and treatment outcomes. The proprietary platform powers the first multimodal machine learning models trained to predict patient response across disease indications to rapidly identify patients more likely to respond favorably to a new drug. Utilizing Valinor’s platform, drug developers can distinguish responders from non-responders while surfacing novel biology associated with response that can reframe target patient populations, and uncover potential new indications based on real-world patient data.

“As early backers of tech bio pioneers like Recursion, we’ve seen AI become the driving force accelerating the next generation of drug development. Valinor pushes the frontier further with an AI-first, disease-focused platform training on exceptional clinical data. We believe this approach can meaningfully improve clinical trial success,” said Brittany Walker, General Partner at CRV.

With this financing, Valinor will further expand its proprietary datasets and recruit additional top-tier machine learning talent to expand the company’s San Francisco-based team.

Follow Valinor on LinkedIn and X, and visit ValinorDiscovery.com to learn more about Valinor’s approach or collaborate on customized patient selection models for specific assets, diseases, or clinical endpoints.

About Valinor

Valinor is revolutionizing therapeutic R&D by using machine learning combined with proprietary clinical datasets. Valinor is currently developing a suite of patient-derived datasets and predictive models to empower drug developers to predict patient response. By reducing trial-and-error and de-risking development, Valinor aims to accelerate breakthroughs across therapeutic areas and drug modalities.

Contacts

Media Contact: 
Eric Schudiske
eric@bioscribe.com

Company Contact: 
Joshua Pacini
josh@valinordiscovery.com 
LinkedIn: www.linkedin.com/in/joshua-pacini-0548351aa/ 
X: www.x.com/joshpacini

SOURCE

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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