By shifting from animals to an exclusively human optimization preclinical process, Vivodyne has raised $40 million in new Series A financing to scale its robotics+AI approach to testing on thousands of lab-grown, fully-functional human tissues, and the massive amount of human data they generate. With the new financing, Vivodyne will open a 23,000-square-foot fully robotic laboratory at Genesis Marina in South San Francisco.

通过从动物实验转向专注于人类优化的临床前流程，Vivodyne 在新一轮 A 轮融资中筹集了 4000 万美元，用于扩大其机器人+人工智能方法的应用规模，对数千个实验室培育的、功能齐全的人体组织进行测试，并处理这些组织生成的海量人类数据。借助这笔新资金，Vivodyne 将在南旧金山的 Genesis Marina 开设一个 23,000 平方英尺的全机器人实验室。

The new facility significantly increases preclinical human testing capacity to meet surging demand from global pharmaceutical clients, particularly spurred on by the recent commitments by FDA and NIH to move away from less-predictive animal models..

新设施大幅增加了临床前人体测试能力，以满足全球制药客户激增的需求，特别是受到FDA和NIH最近承诺放弃较低预测性的动物模型的推动。

The investment was led by Khosla Ventures, with participation from new investors Lingotto Investment Management, Helena Capital, Fortius Ventures, and existing investors Kairos Ventures, CS Ventures, Bison Ventures, and MBX Capital.

本轮融资由科斯拉创投领投，新投资者灵格托投资管理公司、海伦娜资本、福蒂厄斯创投，以及现有投资者凯罗斯创投、CS创投、野牛创投和MBX资本参与。

Vivodyne is rendering inaccurate animal testing obsolete, using automated robotic platforms and AI to grow and analyze thousands of fully functional human tissues. Pharmaceutical companies historically have spent millions on clinical trials destined to fail 95% of the time because animal models are poor predictors of human biology.

Vivodyne正在通过使用自动化机器人平台和人工智能来培养和分析数千个完全功能性的人体组织，从而使不准确的动物测试变得过时。制药公司历来在注定95%会失败的临床试验上花费数百万，因为动物模型对人类生物学的预测能力较差。

Vivodyne solves this problem by providing unprecedented, clinically relevant human data at massive scale. Already used by most top pharma companies, Vivodyne's platform significantly reduces trial risk, accelerates drug discovery, and brings safer, more effective therapies to patients faster..

Vivodyne通过提供前所未有的、大规模的临床相关人类数据来解决这一问题。目前已被大多数顶级制药公司使用，Vivodyne的平台显著降低了试验风险，加速了药物发现，并更快地为患者带来更安全、更有效的治疗方法。