Innovation

The Science Behind SMRTvax

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We use advanced causal machine learning models to predict individual vaccine responses with high confidence, making us one of the only teams delivering this level of accuracy in a healthcare-ready setting.

We require no blood, genetic, or physical tests to assess immune fitness. Our AI model achieves +90% prediction accuracy using existing patient data alone, providing a highly cost-efficient and scalable solution for healthcare settings.

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SMRTmeds uses machine learning to predict individual vaccine responses and optimise schedules. Integrated with healthcare records, it provides personalised recommendations and improves population-wide vaccine outcomes as more data becomes available.

How It Works:

1. Electronic Healthcare Record Integration:

Our software integrates digital clinical data such as those present in EHR.

2. AI-Driven Analysis:

Machine learning models trained on multi-vaccine datasets (flu, COVID-19, malaria) optimize booster timing.

3. Prediction of immune durability and booster scheduling:

A platform integrated into your healthcare system that will indicate whether you should take a second dose and, if so, when you should get it.

Scientific Validation

Validated in Stanford’s systems vaccinology study

 (Cortese M et al. Nature Immunology, 2025).

Integrated with HIPC Immune Signatures Data Resource for cross-vaccine accuracy

(Diray-Arce J et al. Scientific Data, 2022).

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