Preview Health

AI-powered molecular profiling for precision medicine.

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At a glance

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    Development stage

    Active / generating revenue

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    Investment stage

    Pre-Seed

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    UNSW affiliation

    Staff research & technology

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    Technology readiness level

    TRL-6

  • Gender female icon
    Female led

    Yes

Why invest
We map 100% of metabolites, compared to the <1% analysed by competitors, to create molecular fingerprints, offering unmatched Parkinson’s insights. Now attracting pharma interest across disease areas.

Preview Health is pioneering AI-powered ‘molecular fingerprints’ for precision medicine.

Using AI and chemical methods, its proprietary technology analyses tens of thousands of metabolites. Unlike competitors who analyse <1%, Preview Health captures 100%, enabling earlier, more complex disease detection and comprehensive drug response profiling required for precision medicine.

  • Preview Health’s AI-powered platform analyses 100% of metabolite data in clinical trials to understand why some individuals respond to a drug in a particular way. By identifying new biomarkers, it can more accurately evaluate drug response. It can also use any biological sample type and be applied to any disease. Samples are shipped to its lab, where metabolic data is extracted using specialised mass spectrometry and advanced AI methods.

    • Clinical trials fail due to limited biomarkers that don’t reflect real disease biology.
    • Existing clinical trial endpoints miss subtle drug effects or patient differences, leading to failed trial outcomes.
    • Current metabolic analysis techniques analyse <1% of available data, missing key indicators of drug response.
    • Pharma wastes billions on failed Phase 2/3 trials with over 90% of diseases remaining without a cure.
    • Pharmaceutical and biotech companies running Phase 2 or 3 clinical trials in rare diseases, neurology, immunology, or gastrointestinal diseases
    • Selected as Top 12 global startup in pharma-sponsored accelerator in the US
    • Published study identifying novel metabolites predicting early Parkinson’s with 96% accuracy
    • Pilot study with mid-sized diagnostics lab demonstrating 98% precision in identifying two chronic pain subtypes

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