What You Should Know:

你应该知道的：

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Brooklyn Health

布鲁克林健康

, a neuroscience technology company focused on objective measurement of mental health announced it has secured $6.5M in seed funding led by

，一家专注于心理健康客观测量的神经科学技术公司宣布，它已经获得了由...领投的650万美元种子资金

HealthX

健康科技

, with participation from

，参与方包括

Metrodora Ventures

米特罗多拉风险投资公司

,

，

Story Ventures

故事创投

,

，

RiverPark Ventures

河畔公园创投

,

，

Laconia Capital,

拉科尼亚资本，

Everywhere Ventures

遍地风险投资

,

，

Hypothesis Studio

假设工作室

,

，

Blue Falcon Capital,

蓝隼资本，

and others.

和其他人。

– The funding coincides with the company’s debut of its new electronic clinical outcome assessment (eCOA) solution, Willis. Willis is a comprehensive measurement platform that automates legacy services through artificial intelligence (AI), aiming to ease access to critical tools necessary for successful drug development in Central Nervous System (CNS) clinical trials..

– 这笔资金与公司新推出的电子临床结果评估（eCOA）解决方案Willis同时发布。Willis是一个综合测量平台，通过人工智能（AI）实现传统服务的自动化，旨在为中枢神经系统（CNS）临床试验中成功的药物开发提供必要的关键工具访问便利。

Tackling the Measurement Crisis in Neurology and Psychiatry

应对神经病学和精神病学中的测量危机

Clinical trials for CNS conditions traditionally rely on clinical interviews as the primary outcome measure for treatment efficacy. These interviews allow for the scoring of symptoms through observation and are vital for measuring changes in response to treatment. However, this method faces significant challenges: clinical interviews are difficult to standardize, and scoring is often subjective and susceptible to biases.

中枢神经系统疾病的临床试验传统上依赖临床访谈作为治疗效果的主要评估指标。这些访谈通过观察来对症状进行评分，是衡量治疗反应变化的重要手段。然而，这种方法面临重大挑战：临床访谈难以标准化，且评分往往主观性强，容易受到偏见影响。

This can lead to unreliable outcome measures and is associated with placebo response, both of which are major contributors to the high failure rate of CNS clinical trials, costing the industry billions of dollars annually..

这可能导致结果指标不可靠，并与安慰剂反应相关，这两者都是导致中枢神经系统临床试验高失败率的主要因素，每年给行业造成数十亿美元的损失。

“Measurement is a core issue in neurology and psychiatry,” said Dr. Anzar Abbas, neuroscientist, CEO and founder of Brooklyn Health. “Clinical interviews, the standard for symptom assessment, are fundamentally unreliable and imprecise. Our mission at Brooklyn Health is to solve this measurement problem through accurate, sensitive and objective measures of mental health, lowering the barrier for drug discovery and enabling precision care”..

“测量是神经学和精神病学的核心问题，”布鲁克林健康公司的神经科学家、首席执行官兼创始人安扎尔·阿巴斯博士说。“临床访谈作为症状评估的标准方法，从根本上来说是不可靠且不精确的。我们在布鲁克林健康的使命是通过准确、敏感和客观的心理健康测量手段来解决这一测量问题，降低药物研发的门槛，并实现精准护理。”

Willis: AI-Powered Precision for Clinical Trial Endpoints

威利斯：人工智能驱动的临床试验终点精准化

Brooklyn Health’s Willis platform directly addresses these challenges through

布鲁克林健康的威利斯平台直接通过以下方式应对这些挑战

AI-powered

人工智能驱动的

review of clinical interview quality and score accuracy. This gives clinicians real-time feedback on interview administration and provides pharmaceutical sponsors with unprecedented visibility into data quality at scale. Prior to Willis, such interview review was an entirely manual process, making it impractical and prohibitively expensive for most study sponsors..

临床访谈质量与评分准确性的审查。这为临床医生提供了关于访谈实施的实时反馈，并为制药赞助商提供了前所未有的大规模数据质量可视性。在Willis之前，这种访谈审查完全是一个手动过程，对大多数研究赞助商来说不切实际且成本过高。

Willis also represents a significant modernization of the eCOA platform itself. It features an intuitive user experience, native clinician training, real-time flagging of concerning events, powerful data analytics, and streamlined communication channels between clinical sites and pharmaceutical sponsors, all built on a secure and scalable cloud architecture..

Willis还代表了eCOA平台本身的显著现代化。它具有直观的用户体验、原生的临床医生培训、对值得关注的事件进行实时标记、强大的数据分析功能，以及临床站点和制药赞助商之间简化的沟通渠道，所有这些都建立在安全且可扩展的云架构之上。

Open-Source Foundation: The Role of OpenWillis

开源基础：OpenWillis 的作用

Central to Brooklyn Health’s innovative approach is OpenWillis, an open-source Python library for digital phenotyping, which serves as the foundation of its measurement technology. Unlike competitors that often rely on proprietary algorithms, Brooklyn Health has made its core methods available to the scientific community.

布鲁克林健康中心的创新方法核心是 OpenWillis，这是一个用于数字表型分析的开源 Python 库，也是其测量技术的基础。与常依赖专有算法的竞争对手不同，布鲁克林健康中心已将其核心方法开放给科学界使用。

OpenWillis provides researchers with a simple toolkit for quantifying facial emotions, voice and speech characteristics, motor functioning, and other behavioral indicators of mental health. This bridges the gap between academic research and clinical applications, fostering a community-driven approach to the validation of novel methods in digital phenotyping..

OpenWillis 为研究人员提供了一套简单的工具包，用于量化面部情绪、声音和语音特征、运动功能以及其他心理健康的行为指标。这弥合了学术研究与临床应用之间的差距，促进了一个社区驱动的方法来验证数字表型分析中的新方法。