AI-POWERED immunology
Enthalpy Bio trains proprietary causal machine learning models using multi-omic, immunological, and clinical data from hospital, clinic, and EHR-linked cohorts. With only demographics, we can forecast how individuals may respond to vaccination — ensuring population-wide protection and reducing healthcare costs.
Cohort intelligence
Immune, omic, and biomarker data unified across clinical records.
RESPONSE inference
Predictive response with AI for new individuals without tests.
Immune prediction
How can AI predict immune responses?
Data collection
Real world data from hospitals, clinics, EHRs, and clinical studies
Causal AI modeling
Proprietary AI model training deconvoluting an immune response
Vaccine optimisation
Individual response prediction and optimisation
Problem Statement
While vaccines protect 99.46% of the population from infection (*COVID-19 data), some vaccinated people can still get infected and develop disease. During the COVID pandemic, treating these individuals costed an estimate of £2,68bn and hundreds of lives, just in the UK alone. Population-level multi-dose vaccine schedules are built for scale, not individual immune differences. The result is an inefficient global system that cannot reliably predict who needs protection, when it’s needed, and how long it lasts.
Schedules are fixed while immunity is dynamic, causing premature boosters or delayed protection, particularly important for high-risk populations.
Without immune prediction, low‑risk good-responding populations may get excess doses while high‑risk low-responding groups miss durable coverage.
Treating vaccinated people costs 10 to 100 million $USD yearly per country due to waning immunity, driving avoidable cost & complexity to healthcare systems.
One-size-fits-all schedule
Personalised Vaccine Schedules
Solution pillars
We train on rich cohort & real world data to build causal models, then deliver personalised predictions for new individuals using EHR data only—no repeated biomarker testing required.
Proprietary causal models trained on cohort immune, multi-omic, and biomarker datasets to predict durability, booster timing, and response with interpretable inference.
Structured patient data, biomarker, and immune profiling across targeted cohorts to fuel model training, validation, and continuous performance benchmarking.
Recommendations for healthcare systems, pharma, and researchers that deliver personalised predictions using biometric EHR-data only once models are trained.
How it works
Our workflow learns from real-world cohorts first, then scales predictions to new individuals without requiring repeated testing for every person.
Why it matters
We train on linked immune, genomic, and clinical data from hospitals or health systems, then use clinical patient attributes to infer immune responses and durability at scale.
Aggregate immune assays, biomarkers, and linked clinical or EHR data from training cohorts across hospitals, clinics, or health systems.
Enthalpy Bio’s causal machine learning pipeline learns the immune durability and vaccine response patterns from the training cohort.
Use EHR data and available patient-level information to infer response and booster timing, without re-testing every person and accounting for missing variables.
Impact & outcomes
Enthalpy Bio improves how vaccine programs are planned and sustained across flu, COVID, HPV, and future immunisation pathways — aligning durability, timing, and population risk with actionable immune prediction.
Global impact
Population-readyQuantify durability at the individual and system level, so health agencies and manufacturers can plan boosters, supply, and risk mitigation with confidence.
A data-driven path to resilient national immunisation programs.
Use cases
Three audience-specific paths to faster evidence and validation, smarter policy, and durable protection.
Clinical trial optimisation & vaccine program design
Predict immune durability to stratify cohorts, sharpen endpoints, and accelerate regulatory-ready evidence with fewer iterations.
Smarter booster policy & resource allocation
Model population-level protection to time boosters, target high-risk groups, and optimise supply with confidence to prevent vaccine stock-outs.
Translational immunology & systems vaccinology
Connect multi-omics and clinical signals to explain immune responses at an individual level and publish high-impact, actionable insights.
About Us
Enthalpy Bio is an Oxford-based team translating complex immune signals into actionable predictions so healthcare systems and biopharma partners can make confident, evidence-led decisions.
The startup began as SMRTmeds and rebranded as Enthalpy Bio in March 2026, reflecting a focused mission to set the global standard for personalised immunisation.
Mission
Building the future of personalised vaccination through AI-driven immune prediction — so every dose is timed, tailored, and trusted.
Our approach fuses systems immunology with advanced machine learning to improve durability, reduce unnecessary boosters, and raise population-level protection and vaccine trust.
We build evidence-first platforms that fit seamlessly into real-world workflows — from cohort design and trial optimisation to long-term immunity management.
Programs & recognitions
Supported by EnSpire Oxford, Oxford Entrepreneurs Network, Oxford Innovation Ecosystem, ENISA, Empresa Nacional de Innovación S.A., APTE, Parque Científico de Madrid, Gobierno de España, and the European Union through NextGenerationEU.
Co-founders
Carlos Valverde Hernandez
BMedSc in Biomedicine — Karolinska Institutet
MSc in Immunology — University of Oxford
Nicholas Raptakis
BSc in Biochemistry — Warwick University
MSc in Pharmacology — University of Oxford
Investors
Enthalpy Bio combines immune prediction and systems vaccinology to optimise booster timing, reduce waste, and unlock long-term population resilience. Our platform is designed for national health systems and global pharma partnerships.
Estimated Market Opportunity (GBP)
UK-only post-regulatory approval Revenue Model (Estimated)
Assumes 10% profit from savings and SOM capture growing from 5%, 10%, 20%, 25%, to 30% across years 1–5.
All values are estimates and subject to validation with partner data.
Expression of Interest
Share your details and preferred agenda. We will respond with availability for a 30-minute strategic update.
Collaboration
We partner with pharmaceutical companies, healthcare systems, and research teams to deploy AI-driven immune prediction, optimise boosters, and accelerate real‑world impact.
Exploring a pilot, a strategic partnership, or investment? Our team will tailor a program that aligns with your clinical, operational, and portfolio goals. Our proprietary AI pipeline can dissect immune responses to individuals, making personalised vaccination a reality.
Direct contact
We welcome partnership inquiries from pharma innovation teams, public health systems, and systems‑vaccinology researchers seeking measurable gains in immune durability.
Share your objectives and timelines — we respond within two business days with next steps and a tailored collaboration plan.
Work with us inquiry
Tell us about your collaboration goals and we will respond within two business days.
Pilot program inquiry
Share your pilot scope, population, and desired outcomes for immune prediction validation.