GenoMe DIagnostics

Rapid Biomarker Discovery

THE CLIENT

GenoME Diagnostics is an award-winning biomarker discovery company based in Belfast, Ireland. They are developing OvaME, a cutting-edge ddPCR-based diagnostic test for ovarian cancer which has the potential to detect changes in the very earliest stages of disease. Their novel diagnostic pipeline can be utilised for biomarker in discovery in a wide range of disease and applications, such as companion diagnostics for patient selection and stratification, disease monitoring, or early diagnosis in other disease areas.

"We had a large number of promising novel biomarkers that we needed to shortlist to a more manageable number, which we planned to take forward for further lab validation and lock-down of the final assay for commercial use."

Shannon Beattie
Shannon Beattie
COO GenoME Diagnostics ​

THE CHALLENGE

GenoME Diagnostics wished to utilize industry-leading machine learning techniques to harness and unlock the full potential of their data assets. With the growing demand for AI and machine learning, companies like GenoME faced difficulties in assembling and retaining specialized data science teams. This posed a risk of missing out on invaluable insights hidden within their molecular data.

"The Sonrai Analytics team were exceptionally helpful. Initially, we did not have a great amount of experience in big data analysis, and the Sonrai team helped to walk us through the platform options and training in a way that was simple to understand, yet professional."

Dr Paul Mullan, Founder,  GenoMe Diagnostics

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THE STRATEGY

Through a strategic partnership with Sonrai Analytics, GenoME Diagnostics seamlessly integrated machine learning into their diagnostic endeavors. By facilitating numerous machine learning experiments across diverse datasets without the need for complex coding, Sonrai Analytics has revolutionized GenoME’s biomarker discovery process.

Sonrai’s platform has expedited the identification and validation of novel biomarkers, enabling GenoME to bypass the need for extensive data science recruitment and resources. This newfound agility empowers GenoME to swiftly navigate the intricate landscape of molecular insights for diagnostic advancements.

  • Assessment: Evaluate GenoMe’s data sources, identify quality issues, and potential biases.
  • Harmonization: Create a framework to integrate different data types.
  • Machine Learning: Design tailored ML pipelines to find diagnostic biomarkers.
  • Data Security: Implement strong privacy measures and access controls.
  • Training: Provide hands-on training and ongoing technical support.
  • Validation: Collaborate to validate results against known biomarkers.
"The results of our engagement with Sonrai has accelerated our validation timeline. It has enabled us to scientifically, logically and reproducibly shortlist our novel potential biomarkers, to only take forward the most promising and differential for further validation in the lab. This has vastly reduced the hands-on time and cost for GenoME Diagnostics product development."
Shannon Beattie
Shannon Beattie
COO GenoME Diagnostics ​

RESULTS

The analysis outputs below are for demonstration purposes. Get in touch to see the full case study with detailed outputs.

Staff saving

Saved Staff Costs

GenoME Diagnostics has achieved remarkable cost efficiency by sidestepping the need to hire additional data science staff, resulting in significant savings in operational expenses.

ML

Reproducible Machine Learning

Over a thousand reproducible machine learning experiments have been seamlessly conducted through Sonrai’s user-friendly platform, empowering GenoME to expedite biomarker discovery.

Save Time

Reduced Time to Discovery

By reducing the time required for insight generation, GenoME has elevated the quality of their diagnostic studies through enhanced data accuracy and validation.

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