Mirae has raised $5.4 million in funding to expand an artificial intelligence-driven continuous care platform for autoimmune diseases and other complex chronic conditions. The round was led by Oxford Science Enterprises.
Mirae is initially focused on inflammatory bowel disease, a group of chronic conditions that includes Crohn’s disease and ulcerative colitis. These diseases can involve unpredictable flares, complicated medication decisions and substantial differences in how individual patients respond to treatment.
The company plans to use AI to capture what patients experience between medical appointments and convert those observations into structured information that clinicians can use when making treatment decisions.
Mirae combines patient-reported information with clinical context and peer-reviewed evidence to create an ongoing view of how a person’s condition is changing.
The company’s approach addresses a limitation of episodic healthcare. Patients with chronic conditions may see their clinicians only periodically, even though their symptoms, medication responses, daily behaviors and disease activity can change continuously.
During an appointment, clinicians may need to reconstruct several weeks or months of health history using fragmented notes and the patient’s memory.
Mirae is designed to collect that information as events occur, creating a longitudinal record that may help patients and clinicians identify trends earlier.
The platform builds on research from the University of Oxford’s Computational Health Informatics Lab, where Mirae co-founder Dr. David Clifton has led work involving disease progression and large-scale longitudinal clinical data.
Longitudinal data follows patients over time rather than examining information from only one appointment or test. This can help researchers and clinicians identify patterns involving symptom development, treatment response and disease progression.
Mirae is being deployed with a major U.S. health system, giving the company access to real-world patient information that can support the development and validation of its models.
The company did not identify the participating health system.
For patients, Mirae operates as a conversational AI companion that can receive everyday information in plain language.
Users can describe symptoms, medication use, daily activities, behavioral changes and other developments without having to organize the information into formal medical categories.
The system asks follow-up questions, tracks patterns and builds an evolving record of the patient’s condition.
As more information accumulates, the platform can help users understand which activities or circumstances tend to accompany symptoms, how they have responded to treatments tend to accompany and what has changed since a previous medical visit.
Mirae can also summarize important trends before an appointment, helping patients communicate more clearly with their care teams.
For clinicians, the platform provides an AI copilot that brings together symptom patterns, treatment history, laboratory data and other patient-specific information.
The resulting view is intended to give clinicians a more current understanding of the disease than they might obtain from isolated appointments or incomplete patient recall.
This could allow providers to spend less time reconstructing what happened between visits and more time evaluating treatment options, adjusting medications or determining whether additional testing is required.
Mirae also intends to support ongoing monitoring as new signals emerge.
Earlier identification of changes can be especially important in inflammatory bowel disease because symptoms may worsen before the patient receives a scheduled evaluation.
A continuous system could potentially help patients recognize a developing flare sooner and contact their medical team before the condition requires emergency or hospital-based treatment.
Mirae’s broader objective is to make specialty-level clinical decision support more widely available.
Patients with complex chronic conditions often receive different levels of care depending on their location, access to specialists and the resources of their healthcare organization.
Major academic medical centers may have multidisciplinary teams with extensive experience treating difficult cases. Patients in other areas may have limited access to that expertise.
Mirae is seeking to help clinicians deliver care that more closely reflects a center-of-excellence standard by combining continuous patient data with validated medical evidence.
The company is not positioning its technology as a replacement for clinicians. Its platform is designed to organize information, surface relevant patterns and support medical professionals as they make final treatment decisions.
This distinction is important because symptoms associated with autoimmune diseases can be complex and may overlap with infections, medication side effects or other health conditions.
Mirae said its model could also shift more high-quality care into outpatient settings by enabling earlier and more consistent intervention.
Outpatient care is generally less expensive and disruptive than inpatient treatment. Preventing a severe flare or identifying ineffective treatment earlier could potentially reduce emergency visits, hospital admissions and productivity losses.
The company cited estimates suggesting chronic disease could cost the United States as much as $47 trillion over the next 15 years, with combined medical and productivity losses approaching $13,000 per person.
Those figures illustrate the economic burden of diseases that require years of monitoring and treatment, although Mirae’s announcement did not provide the underlying source or methodology.
CEO and co-founder Anuj Patel said a major limitation of current AI models is that the day-to-day experience of living with a disease rarely enters the clinical record in a structured and usable form.
He believes combining experiential information with clinical data can support more accurate disease models and create a path toward precision medicine.
Precision medicine seeks to tailor treatment based on the characteristics of an individual patient rather than relying only on broad population averages.
For autoimmune diseases, this could include evaluating how symptoms, laboratory findings, medication history and behavioral factors interact over time.
Oxford Science Enterprises Health Tech Principal Joel Schoppig said the most significant healthcare applications of AI may emerge in areas where diseases change over time and incorrect decisions carry substantial consequences.
He said Mirae is building at the intersection of patient context, clinical evidence and healthcare workflows rather than creating a broad, general-purpose AI tool.
With the new funding, Mirae plans to continue developing its technology, validating its models and expanding its clinical deployment.
KEY QUOTES:
“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.”
“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.”
Anuj Patel, Co-Founder and Chief Executive Officer of Mirae
“AI is moving quickly into healthcare, but much of that activity remains broad, generalized, and disconnected from the clinical decisions that determine outcomes.”
“Its greatest impact will come from areas where decisions are complex, conditions evolve, and the cost of getting those decisions wrong is high. 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.”
Joel Schoppig, Health Tech Principal at Oxford Science Enterprises
