Machine learning for diagnostics design

Our molecular diagnostic target identification and synthetic biology design processes are powered by innovative bioinformatics and machine learning approaches

The combination of synthetic biology and advanced bioinformatics approaches drives our continued innovation, and is applicable to all molecular diagnostic technologies.

Non-biased high throughput target identification 

Using bioinformatics workflows, we can identify molecular diagnostic targets optimised for desired characteristics. This allows us to find genetic targets with specificity to multiple strains or species or to a single pathogen as required.

Synthetic biology designed through machine learning

Using machine learning we have developed an automated method for designing synthetic nucleic acid polymers which work in combination to detect target genetic sequences with desired specificity and high sensitivity.

Highly automated

Our process from target identification to molecular diagnostic design is highly automated enabling rapid and high throughput diagnostic test design at scale. This enables both a quick turnaround for partnering companies and a rapid pace of diagnostic innovation.

Find out how our bioinformatics technology can aid your diagnostics design:

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