人工智能技术研究商Valinor Discovery筹集1300万美元种子轮融资，利用专有机器学习模型提高临床试验成功率-动脉网

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

vcaonline 等信源发布 2025-12-11 23:51

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

瓦里诺尔筹集1300万美元，利用专有机器学习模型提高临床试验成功率

Funding will further scale the company’s multimodal ML platform for patient selection

资金将进一步扩大公司用于患者选择的多模态机器学习平台规模。

SAN FRANCISCO, December 11, 2025-- Valinor, a pioneering AI company leveraging advanced machine learning models to increase the probability of clinical trial success by deeply understanding patient response, today announced $13 million in funding. The seed funding was led by CRV, Harpoon Ventures, Amino Collective, and Pelion Venture Partners.

旧金山，2025年12月11日——Valinor，一家利用先进机器学习模型深入理解患者反应以提高临床试验成功率的先锋人工智能公司，今天宣布获得了1300万美元的融资。这笔种子资金由CRV、Harpoon Ventures、Amino Collective和Pelion Venture Partners领投。

Other participants include numerous leading angel investors and operators such as Charlie Songhurst, Surya Midha (co-founder of Mercor), Axel Ericsson, and Kyle Harrison..

其他参与者还包括众多领先的天使投资人和运营商，如查理·宋赫斯特、苏里亚·米达（Mercor 的联合创始人）、阿克塞尔·埃里克森和凯尔·哈里森。

“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.

“我们的模型旨在揭示患者反应背后的有意义的特征。我们相信，这种方法将助力我们的制药合作伙伴提高临床试验成功率、降低研发成本，并且最重要的是，加速将救命药物送到患者手中，”Valinor创始人兼首席执行官Joshua Pacini表示。

“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.”.

“通过这笔资金，我们正在加速扩展我们专有的匹配组学和临床结果数据集，并推进我们的AI模型，使我们的制药合作伙伴能够在药物开发中做出更明智、数据驱动的决策。”

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.

瓦利诺尔的模型是基于患者来源的多组学样本和治疗结果的匹配数据集训练而成。该专有平台支持首个跨疾病适应症预测患者反应的多模态机器学习模型，能够快速识别更有可能对新药产生良好反应的患者。

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..

利用瓦林诺尔的平台，药物开发者可以区分有反应者和无反应者，同时揭示与反应相关的新生物学机制，从而重新定义目标患者群体，并基于真实世界的患者数据发现潜在的新适应症。

“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..

“作为像Recursion这样的技术生物先驱的早期支持者，我们已经看到人工智能成为推动下一代药物开发的驱动力。Valinor通过一个以人工智能为先导、专注于疾病的平台，利用卓越的临床数据进行训练，进一步拓展了这一领域。我们相信这种方法可以显著提高临床试验的成功率，”CRV的普通合伙人布列塔尼·沃克表示。

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.

通过这笔融资，Valinor 将进一步扩充其专有数据集，并招募更多顶级机器学习人才，以扩大公司位于旧金山的团队。

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.

在LinkedIn和X上关注瓦林诺，并访问ValinorDiscovery.com以了解更多关于瓦林诺的方法，或合作开发针对特定资产、疾病或临床终点的定制患者选择模型。

About Valinor

关于瓦林诺

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..

瓦林诺尔正在通过使用机器学习结合专有临床数据集来彻底改变治疗研发。瓦林诺尔目前正在开发一套患者衍生的数据集和预测模型，以帮助药物开发者预测患者反应。通过减少试错并降低开发风险，瓦林诺尔旨在加速各个治疗领域和药物模式的突破。

Contact:

联系人：

Media Contact:

媒体联系人：

Eric Schudiske

埃里克·舒迪斯ке

eric@bioscribe.com

Company Contact:

公司联系人：

Joshua Pacini

约书亚·帕奇尼