Anuj Patel (opens in a new tab)
Founder & CEO
Anuj previously founded Motto Health, a virtual care company for autoimmune conditions, after leading product at PatientsLikeMe and iCarbonX.
Mirae maps the fastest way to remission. We are building an everyday guide that helps people understand their disease, see possible patterns, ask sharper questions, and prepare for care without turning life into a spreadsheet.
The goal is not more data for its own sake. It is more agency for patients and a clearer picture to bring into clinical care.
Mirae is available now on iOS and Android. We are still building, learning, and refining, which is why feedback from people living with inflammatory bowel disease matters: what feels useful, what feels like nonsense, and what would make Mirae worth opening again.
Clinical information such as tests, markers, diagnoses, and medications tells one part of the story. Daily experience such as symptoms, routines, pain, fatigue, fears, and tradeoffs tells another. Understanding inflammatory bowel disease as it relates to you takes both.
People deserve direct answers in plain language. Mirae makes complex information easier to understand without pretending every question has a simple answer.
Mirae helps you prepare for better conversations with your healthcare professionals. It does not diagnose or prescribe, and it never replaces clinical judgment.
We bring together people who have built health products, led technology teams, cared for people with IBD, and advanced medical research.
Founder & CEO
Anuj previously founded Motto Health, a virtual care company for autoimmune conditions, after leading product at PatientsLikeMe and iCarbonX.
Founder & CTO
James co-founded and served as CTO of mPharma, the African health company serving millions annually and recognised with the 2019 Skoll Award for Social Entrepreneurship.
Academic Co-Founder
Royal Academy of Engineering Chair of Clinical Machine Learning, University of Oxford
David leads Oxford’s Computational Health Informatics Lab and was the first non-medical scientist appointed to an NIHR Research Professorship.
Founding Designer
Sayoko brings product design leadership from Grubhub, where she directed experiences across its consumer, merchant, delivery, and care products.
Founding Engineer
Robert creates open-source tools used by React Native developers, including TypeScript bindings that connect apps with Apple HealthKit.
Founding Engineer
Selasie previously served as CTO of mPharma, rising from software engineer to lead the technology behind its expanding African health network.
Founding Engineer
Hamza founded GitStart, a Y Combinator-backed developer platform, after working on Microsoft Azure and building technology teams across several continents.
Founding Operator
Filiberto brings 15 years of experience running finance, operations, and people for founders and venture-backed companies.
Postdoctoral Researcher
University of Oxford
Yixuan researches vision-language models and trustworthy machine learning for healthcare, with a focus on medical understanding and data privacy.
Senior Research Associate
University of Oxford
Yujiang previously researched at Meta and Microsoft Research Asia and now co-leads Oxford’s Digital Health Group in Suzhou.
Clinical Advisor
Alissa is an Oxford consultant gastroenterologist and founder of Crohn’s Colitis Cure, with research spanning digital monitoring and patient-centred IBD care.
Clinical Advisor
Simon is a former president of ECCO whose IBD measures and research have shaped international guidelines, clinical trials, and everyday care.
Health Systems Advisor
David is a physician and healthcare leader whose career spans clinical care, Mayo Clinic, payer strategy, venture building, and health systems design.
Work spanning medical AI, health data, patient communication, and inflammatory bowel disease.
A structured approach to learning across different kinds of health records while allowing data to remain with the organisations that hold it.
Thakur et al., AAAI
A way for healthcare organisations with different views of patient data to contribute to shared model learning.
Thakur et al., npj Digital Medicine, 2024
Research into making large clinical datasets much smaller while preserving useful patterns for medical AI research.
Wang et al., arXiv, 2023
An invention for reducing very large healthcare datasets into small, portable forms that conceal individual patient information and make AI training easier.
Registered invention
A method that draws on relevant examples and medical knowledge to generate clearer, more faithful patient instructions.
Liu et al., NeurIPS, 2022
Research into recognising when breathing measurements derived from common heart and pulse signals are reliable enough to use.
Birrenkott, University of Oxford, 2015
A research system that combines language models with hundreds of established clinical risk tools.
Liu et al., medRxiv preprint, 2025
A foundation model designed to learn from heart signals across different devices and settings, from hospitals to home monitoring.
Gu et al., Nature Machine Intelligence, 2026
Research into grounding reports generated from clinical tables in retrieved evidence and medical knowledge.
Research project
An exploration of how people with ulcerative colitis experience regular digital symptom monitoring and the sense of agency it can create.
Walsh, Matini, Hinds et al., Intestinal Research, 2019
A practical review of the different ways clinicians assess IBD, from symptoms and biomarkers to endoscopy and quality of life.
Walsh, Bryant & Travis, Nature Reviews Gastroenterology & Hepatology, 2016
Research identifying a group of people with IBD whose immune systems block an important inflammation-regulating signal.
Gharahdaghi et al., New England Journal of Medicine, 2026
Research into a signal linked to intestinal inflammation and why some people may not respond to anti-TNF treatment.
West et al., Nature Medicine, 2017
Bring your symptoms, food, medications, lab results, and questions together so you can understand what is changing and prepare for your next care conversation. Mirae is always free for patients. There is no paid patient plan, no trial period, and no card needed to start using the app.