Serox's data-centric approach is designed to take IVD on the journey through regionalisation to personalisation.
Serox detects disease by identifying unique ‘biochemical fingerprints’ in biological fluids, such as urine and plasma.
Serox doesn’t target individual biomarkers: it takes the aggregated Raman response of all the metabolic compounds found in the sample.
Serox uses SERS to focus on subsets of metabolic compounds which are known to be associated with disease and enhance their signal by orders of magnitude.
Serox uses Machine Learning algorithms to build disease specific models from these unique biochemical fingerprints.
Use urine instead of blood, imaging or biopsy.
A result within 3 minutes.
Total workflow cost an order of magnitude less.
Urine contains metabolites that provide multiple biomarkers of disease within the metabolic 'soup' that is urine.
The spectrometer obtains the aggregated response from the ensemble of biomarkers contained in this metabolic soup.
Raman Spectroscopy allows discrimination between diseased and non-diseased samples. The signal can be enhanced using SERS.
The response of all metabolites is aggregated. Serox uses Machine Learning to isolate the target signals and categorise the output.
The resulting model allows clinical users to differentiate between diseased and non-diseased samples and is embodied within software.
Multiple diagnoses are viable from a single sample. The cartridge can be optimised for target diseases.
We can use our lower-cost multi-test capability to offer 'panels' of tests that deliver to the needs of clinical specialisms, a stage in life, or where one symptom may currently require multiple tests.
Serox Ltd
Unit 22, Hanborough Business Park Oxford,
OX29 8LH
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