Breaking the cycle of uncertainty and guesswork for those living with autoimmune disease and other complex chronic conditions, Mirae's AI companion turns day-to-day signals into a living medical library, helping patients understand their condition, catch flares earlier, and make more informed care decisions.

Mirae 的 AI 伴侣打破了自身免疫性疾病及其他复杂慢性病患者所面临的不确定性与猜测循环，将日常信号转化为动态更新的医学知识库，帮助患者更好地理解自身病情、更早发现发作迹象，并做出更明智的护理决策。

Every clinician can now deliver care to a center-of-excellence standard, supported by Mirae's continuous patient data and validated, peer-reviewed evidence, enabling earlier detection, more accurate assessment, and more precise treatment decisions

如今，在Mirae提供的连续患者数据以及经过验证、同行评审的证据支持下，每位临床医生都能提供达到卓越中心标准的医疗服务，从而实现更早的检测、更准确的评估和更精准的治疗决策。

Mirae's AI-driven model shifts superior outcomes out of expensive inpatient settings and into everyday outpatient practice, allowing high-quality care to be delivered earlier, more consistently, and without reliance on hospital-based intervention

Mirae 的 AI 驱动模型将更优的治疗结果从昂贵的住院环境转移至日常门诊实践，使得高质量护理能够更早、更一致地提供，且无需依赖医院干预。

NEW YORK

纽约

,

，

July 28, 2026

2026年7月28日

/PRNewswire/ --

/美通社/ --

Mirae

未来

, an AI-driven continuous care platform for autoimmune disease and other complex chronic conditions, today announced $5.4 million in funding led by Oxford Science Enterprises. Mirae captures what patients experience between visits and converts it into a

，一个由人工智能驱动的针对自身免疫性疾病及其他复杂慢性病的连续护理平台，今日宣布获得由牛津科学企业领投的540万美元融资。Mirae 捕捉患者在就诊间隔期的体验，并将其转化为

continuous, structured view of disease

疾病的连续、结构化视图

that clinicians can act on at the point of care, combining patient-reported data with clinical context and peer-reviewed evidence to support more informed, timely treatment decisions.

使临床医生能够在诊疗现场采取行动，将患者报告的数据与临床背景及经同行评审的证据相结合，以支持更加明智、及时的治疗决策。

Mirae builds directly on research from the

Mirae 直接基于来自

University of Oxford's Computational Health Informatics Lab

牛津大学计算健康信息学实验室

, where co-founder

，其中联合创始人

Dr. David Clifton

大卫·克利夫顿博士

has led work in modeling disease progression using large-scale, longitudinal clinical data. The company is initially focused on inflammatory bowel disease (IBD), a condition marked by unpredictable flares, complex medication decisions, and highly variable treatment responses. The platform is being deployed with a leading U.S.

已领导利用大规模纵向临床数据对疾病进展进行建模的工作。公司最初专注于炎症性肠病（IBD），该病的特点是发作不可预测、用药决策复杂以及治疗反应高度可变。该平台正在美国一家领先的医疗机构中部署。

health system, providing ongoing access to real-world patient data to support model development and validation..

卫生系统，提供对真实世界患者数据的持续访问，以支持模型的开发和验证。

Autoimmune disease and other complex chronic conditions place a high burden on both patients and health systems because they evolve continuously but are managed episodically. Chronic disease could cost the U.S. up to

自身免疫性疾病和其他复杂的慢性疾病给患者和医疗系统带来了沉重负担，因为这些疾病持续进展，却仅得到间歇性管理。慢性病可能给美国带来高达

$47 trillion over the next 15 years

未来15年内达47万亿美元

, with medical and productivity losses contributing to nearly

，其中医疗和生产力的损失占了近

$13,000 per American

每位美国人13,000美元

. Yet care is still delivered through infrequent visits that provide only limited snapshots of a patient's condition, leaving patients to manage their disease day to day without structured support, and clinicians to make decisions without visibility into how symptoms, behaviors, and treatment responses evolve..

然而，目前的医疗护理仍依赖于频率较低的就诊，仅能提供患者状况的有限片段，导致患者在缺乏结构化支持的情况下自行应对日常疾病管理，而临床医生也因无法全面了解症状、行为及治疗反应的演变过程，难以做出精准决策。

'Where you live should not dictate the quality of care you receive. A lot of the variability in care and outcomes comes from the fact that clinicians are working without a full view of what has happened between visits' said Anuj Patel, co-founder and CEO of Mirae. 'The limitations of AI in understanding and modeling complex disease comes from the fact that patients are living with their disease every day, but that experience rarely makes it into the clinical record in a usable way.

“您居住的地方不应决定您所接受的护理质量。护理和结果中的许多差异源于临床医生在就诊间隙缺乏对患者情况的全面了解。”Mirae 的联合创始人兼首席执行官 Anuj Patel 表示。“人工智能在理解和建模复杂疾病方面的局限性，源于患者每天都在与疾病共存，但这种日常经历很少以可用的形式被纳入临床记录中。”

When you combine experiential data with clinical data, you begin to understand and model disease more effectively and have a path towards true precision medicine. Every patient deserves access to world class decision-making for their care and the tools to take ownership over their condition between visits.'.

当您将体验数据与临床数据相结合时，您便能更有效地理解和建模疾病，并走上实现真正精准医疗的道路。每位患者都应享有获得世界级诊疗决策支持的权利，并拥有在就诊间隔期主动管理自身健康状况的工具。

For patients, Mirae is designed to fit into daily life, turning small, everyday inputs into something clinically meaningful. People can describe symptoms, daily behaviors, medications, and changes in plain language as they happen, without needing to actively structure or organize. Mirae's conversational AI asks follow-up questions, tracks patterns, and builds a continuous record of how their condition is evolving.

对于患者而言，Mirae 旨在融入日常生活，将微小的日常输入转化为具有临床意义的数据。人们可以用平实的语言随时描述症状、日常行为、用药情况及变化，无需主动进行结构化或整理。Mirae 的对话式人工智能会提出跟进问题，追踪模式，并建立一份关于病情演变的连续记录。

As that history builds, it helps patients understand what tends to trigger symptoms, how they've responded to treatment, and what has changed. It also prepares them for care moments by summarizing key trends, making it easier to have more informed conversations with their care team..

随着病史的逐步积累，它有助于患者了解通常引发症状的因素、他们对治疗的反应以及发生的变化。它还通过总结关键趋势，帮助患者为就医时刻做好准备，从而更轻松地与医疗团队进行更有依据的沟通。

For clinicians, Mirae's AI copilot provides a structured, up-to-date view of what has happened between visits, bringing together symptom trajectories, treatment history, lab data, and other inputs into a single, patient-specific picture. Before or during an appointment, clinicians can see how the disease has been evolving, rather than relying on fragmented notes or patient recall.

对于临床医生而言，Mirae 的 AI 辅助工具提供了两次就诊之间发生情况的结构化、最新视图，将症状变化轨迹、治疗历史、实验室数据及其他输入信息整合为一份针对特定患者的全景画像。在预约前或就诊期间，临床医生可以了解疾病的演变过程，而不再依赖零散的病历记录或患者的回忆。

This shifts time away from reconstructing the patient's history and toward evaluating treatment options and next steps, while also supporting ongoing monitoring as new signals emerge..

这将时间重心从重建患者病史转向评估治疗方案和后续步骤，同时随着新信号的出现，支持持续监测。

'AI is moving quickly into healthcare, but much of that activity remains broad, generalized, and disconnected from the clinical decisions that determine outcomes,' said Joel Schoppig, Health Tech Principal, Oxford Science Enterprises. 'Its greatest impact will come from areas where decisions are complex, conditions evolve, and the cost of getting those decisions wrong is high.

牛津科学企业公司健康科技负责人乔尔·肖皮格表示：“人工智能正迅速进入医疗保健领域，但其中许多应用仍然宽泛、通用，且与决定诊疗结果的临床决策脱节。”“其最大影响将来自那些决策复杂、病情动态变化且误判代价高昂的领域。”

Mirae is building for this deeper layer of medicine, where patient context, clinical evidence, and workflow need to come together to support a higher standard of care.'.

Mirae 正在为医学的更深层面构建解决方案，在这一层面中，患者背景、临床证据和工作流程需要紧密结合，以支持更高标准的医疗护理。

About Mirae

关于未来

Mirae is building a new model for managing autoimmune disease and other complex chronic conditions, starting with inflammatory bowel disease. The company's conversational AI turns everyday patient input into structured, longitudinal insight, enabling earlier intervention and more informed treatment decisions.

Mirae 正在构建一种用于管理自身免疫性疾病及其他复杂慢性病的新模式，并以炎症性肠病为起点。该公司的对话式人工智能将患者的日常输入转化为结构化、纵向的洞察，从而实现更早的干预和更明智的治疗决策。

Developed in collaboration with researchers at the University of Oxford and designed for integration into clinical workflows, Mirae connects patient experience, clinical data, and peer-reviewed evidence into a continuous system of care. By extending the reach of specialty medicine beyond episodic visits, Mirae aims to make high-quality, data-driven care more consistent, more responsive, and more accessible across patient populations.

Mirae 与牛津大学的研究人员合作开发，专为融入临床工作流程而设计，将患者体验、临床数据和同行评审证据连接成一个连续的护理体系。通过将专科医疗的影响范围从单次就诊延伸至更广泛的场景，Mirae 旨在让高质量、数据驱动的护理在不同患者群体中更加一致、响应更及时且更易获得。

Find out more at .

了解更多，请访问。

miraehealth.ai

未来健康.ai

.

。

Media contact

媒体联系人

[email protected]

[email protected]

SOURCE Mirae

来源：Mirae

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