Mirae Launches With $5.4M to Bring AI-Driven Continuous Care to Autoimmune Disease
核心洞察
Mirae (搜索), an AI-driven continuous care platform for autoimmune disease (搜索) and complex chronic conditions, announced $5.4 million in funding led by Oxford Science Enterprises (搜索).
The University of Oxford spinout builds on research from the Computational Health Informatics Lab, with an initial focus on inflammatory bowel disease (搜索) (IBD).
The platform converts everyday patient-reported signals into a structured, longitudinal view of disease to support earlier detection and more informed treatment decisions.
Mirae (搜索), an AI-driven continuous care platform for autoimmune disease (搜索) and other complex chronic conditions, announced $5.4 million in funding led by Oxford Science Enterprises (搜索). The company, a University of Oxford spinout, aims to expand access to world-class specialty care by capturing what patients experience between visits and converting it into a continuous, structured view of disease that clinicians can act on at the point of care.
The platform combines patient-reported data with clinical context and peer-reviewed evidence to support more informed, timely treatment decisions. Mirae (搜索) is initially focused on inflammatory bowel disease (搜索) (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. health system, providing ongoing access to real-world patient data to support model development and validation.
Scientific Foundation and Clinical Rationale
Mirae (搜索) builds directly on research from the University of Oxford's Computational Health Informatics Lab, where co-founder Dr. David Clifton has led work in modeling disease progression using large-scale, longitudinal clinical data. The company was founded by CEO Anuj Patel, James Nishiyama Finucane, and Professor David Clifton, whose research in disease progression modeling provides the algorithmic foundation for Mirae's technology.
Autoimmune disease (搜索) 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 $47 trillion over the next 15 years, with medical and productivity losses contributing to nearly $13,000 per American. 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.
"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 (搜索). "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. 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."
How the Platform Works
For patients, Mirae (搜索) 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. As that history builds, it helps patients understand what tends to trigger symptoms, how they have 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.
For clinicians, Mirae (搜索)'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. 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.
Strategic Perspective
"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 (搜索). "Its greatest impact will come from areas where decisions are complex, conditions evolve, and the cost of getting those decisions wrong is high. Mirae (搜索) 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."
The funding will support the launch and continued development of Mirae (搜索)'s platform as the company seeks to improve access to consistent, data-driven care for people living with complex chronic conditions. 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.