Data-driven Multiplexing for Accurate Gene Detection

Reference number 10730

Sectors: Medtech

Industries: Medical Diagnostics

Machine learning approach for high-level multiplexing in qPCR and dPCR, up to 21-plex demonstrated

The technology enables accurate multiplexing (up to 21 targets in a single well has been demonstrated). The patented approach enables the recognition of primer-characteristic molecular signatures. This gives rise to truly affordable solutions in established molecular tests, by effectively extracting the kinetic and thermodynamic information from existing real-time data. Importantly, this technology is compatible with conventional qPCR and state-of-the-art dPCR set-ups.

Proposed use

This technology enhances diagnostic performance and increases throughput by identifying multiple nucleic acid targets in a single amplification reaction. It is compatible with a wide range of amplification chemistries (e.g., probe-based, intercalating dyes, and isothermal reactions), and hence, can be seamlessly integrated with various laboratory workflows.

Problem addressed

Efficiency and affordability are paramount for a wide range of diagnostic applications including infectious diseases, genotyping and precision cancer medicine. Multiplexing offers a solution that reduces the requirements in physical space, time-to-result, and volume of reagents and sample. To date, multiplexed assays rely on fluorescent probes (limited by optical instrumentation), post-amplification analysis (lengthy gel-electrophoresis or expensive sequencing approaches) or spatial multiplexing (resource consuming).

Technology overview

The technology leverages machine learning to automatically learn target-specific information encoded in each amplification event (via real-time data), to identify the nature of nucleic acid molecules.

Benefits

  • Enables a time and cost-effective solution to identify multiple nucleic acids in a single chemical reaction
  • Provides extremely reliable and accurate high-level multiplexing capability
  • Applies across real-time PCR platforms and amplification chemistries that are used in many scientific fields
  • Identifies millions of single amplification reactions in seconds

Intellectual Property Information

GB 2013035.7 – IDENTIFYING A TARGET NUCLEIC ACID

Contact

Michelle Cortis

Industry Partnerships and Commercialisation Executive, Engineering

Michelle Cortis is an Executive in the Industrial Partnerships and Commercialisation team for the Faculty of Engineering

Contact Michelle

+44 (0) 7517 551971

m.cortis@imperial.ac.uk

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