Oxford Immune Algorithmics Gains Access to 60 million anonymised medical records and Deploys Algocyte® Devices for Testing and Validation with Leading NHS Hospitals in England
London, 31 May 2025 – Oxford Immune Algorithmics® (OIA), a deep-tech spinout from King’s College London (KCL) and Oxford University, has placed a second Algocyte® device at an NHS Foundation Trust at King’s College for testing and validation purposes after collocating its first with Cambridge for the same purposes.
The Algocyte® Mobile Health Station (MHS) is a medical instrument and patented portable blood analyser developed by OIA. It begins by reproducing one of the most widely used and important medical tests—representing the foundation of a sophisticated end-to-end healthcare solution that includes continuous monitoring, health screening, and an advanced early warning system to support differential diagnosis and decision-making for precision healthcare and predictive medicine.
Designed for wide usability beyond traditional lab infrastructure, and ultimately at-home use based on its minimally invasive blood-drawing procedure, the Algocyte® MHS can also operate in clinics, labs, surgeries, hospitals, field units, or mobile health settings. The device leverages multiple complementary imaging technologies, enabling future expansion to additional blood tests. It integrates seamlessly with existing laboratory systems and clinical data sources, including the Algocyte® app, which captures continuous lifestyle events and supplementary clinical information from patients or users.
Thanks to the company’s rigorous security and privacy protocols—certified by multiple and continuously audited ISO standards—Oxford Immune Algorithmics has also signed a licensing agreement with the UK’s Medicines and Healthcare products Regulatory Agency (MHRA) to gain access the world’s largest and highest-quality anonymised NHS patient data repositories.
“OIA’s technology enables us to determine each patient’s personalised ‘baseline’ blood results. Understanding what is ‘normal’ for each individual patient, in addition to how it compares to the whole population, allows us to detect deviations from their baseline more rapidly, potentially long before the patient experiences symptoms. This personalised monitoring could help us become better at detecting disease and knowing whether a patient is responding to a treatment.”
— Prof. Kourosh Saeb-Parsy, Chief Medical Office of OIA, and Honorary Consultant Transplant Surgeon at Cambridge University Hospitals NHS Trust
Advancing Personalised Diagnostics
This access to the NHS dataset includes lifelong records, comprising blood test results and clinical outcomes from over 60 million patients and more than 300 million longitudinal blood test results, instrumental in training and validating the company’s precision healthcare, predictive algorithms and technology stack.
At the core of OIA’s value proposition is vertical integration. By owning and optimising every component—from next-generation diagnostic medical instruments to a powerful AI-driven predictive engine—OIA delivers a seamless, fast, personalised, and clinically actionable user experience.
According to a Nature journal commentary on a recent Harvard group paper, personalised risk identification based on individualised baselines is essential to pinpoint the clinical scenarios where improvements in diagnostic accuracy can truly benefit individuals at scale—an area where genomics and other ‘omics’ approaches have, so far, fallen short:
“For all the talk of “personalized medicine” over the last two decades, potentiated by the human genome sequence, this enriched interpretation of one’s lab test would be simple to implement with further validation and the right computing platform, ideally using multimodal A.I. that integrates the electronic record, labs, scans, and rest of a person’s many layers of data”
— Dr. Eric Topol, Professor of Molecular Medicine, Scripps Research Institute & Top 10 most cited researchers in medicine quoted from Ground Truths.
From Bench to Bedside at Point of Care and Home
Algocyte® represents a shift away from conventional methods that benchmark blood-test results against population averages. This personalised approach addresses a major gap in current diagnostics, where general reference intervals can obscure important individual variations.
OIA’s Algocyte® aims to improve and democratise diagnostic accuracy through smart, personalised, blood-testing-driven monitoring and prediction.
“Instead of relying on average population reference ranges, Algocyte® tracks each person’s unique baseline over time—a metric recently identified by Harvard researchers as a key predictor of health and mortality. Gaining access to this data that adds to our proprietary image repository of 250 thousand labelled cells for AI training, really push the boundaries of personalised healthcare and predictive medicine. By monitoring deviations from people’s baselines, we are proving that our technology can detect early signs of disease and emerging health risks.”
— Dr. Hector Zenil, Founder of OIA and Associate Professor/Senior Lecturer at the School of Biomedical Engineering and Imaging Sciences at King’s College London
The integration of Algocyte® into clinical settings underscores OIA’s commitment to using AI to improve healthcare outcomes at scale. By engaging with NHS partners early, the initiative seeks to bridge existing health equity gaps and advance precision medicine.
OIA has been working and consulting NHS partners since 2019 including running a survey conducted by a large NHS GP surgery in Luton where doctors and nurses said that they could save at least 1-2 hours a week by using a singe automating feature of the Algocyte® app to triage their patients.
The engine behind Algocyte®’s was recently tested against cutting-edge AI systems, including the most advanced LLMs and specialised time-series GenAI predictors showing it can outperform them in model abstraction and predictive capabilities.
Oxford Immune Algorithmics is a deep-tech start-up incubated and co-developed by UK Golden Triangle universities (Oxford, Cambridge, and KCL) that developed Algocyte®, and end-to-end solution for precision healthcare and predictive medicine driven by 15 years of its founder’s research on Artificial Super Intelligence applied to cell and molecular biology.
For further information, visit www.immunealgorithmics.com
To Read More
H. Zenil et al. Causal deconvolution by algorithmic generative models, Nature Machine Intelligence 1, 58–66, (2019). https://www.nature.com/articles/s42256-018-0005-0
Meex and Moberg. Personalized ranges for blood-test results enable precision diagnostics, Nature 637(8045), 279–280, (2024). https://www.nature.com/articles/d41586-024-03854-9
Foy, B. H. et al. Haematological setpoints are a stable and patient-specific deep phenotype, Nature 637, 430–438 (2025). https://pubmed.ncbi.nlm.nih.gov/39663453/
H. Zenil et al. Remodelling machine learning: An AI that thinks like a scientist (YouTube), Nature, https://www.youtube.com/watch?v=rkmz7DAA-t8