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.
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.
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).
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.
- 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
Moniri A, Miglietta L, Malpartida-Cardenas K, Pennisi I, Cacho-Soblechero M, Moser N, Holmes A, Georgiou P, Rodriguez-Manzano J. Amplification Curve Analysis: Data-Driven Multiplexing Using Real-Time Digital PCR. Anal Chem. 2020 Oct 6;92(19):13134-13143. doi: 10.1021/acs.analchem.0c02253. Epub 2020 Sep 18. PMID: 32946688.
Moniri A, Miglietta L, Holmes A, Georgiou P, Rodriguez-Manzano J. High-Level Multiplexing in Digital PCR with Intercalating Dyes by Coupling Real-Time Kinetics and Melting Curve Analysis. Anal Chem. 2020 Oct 20;92(20):14181-14188. doi: 10.1021/acs.analchem.0c03298. Epub 2020 Oct 2. PMID: 32954724.
Lecturer in Antimicrobial Resistance and Infectious Diseases, Faculty of Medicine
PhD in Applied Machine Learning, Faculty of Engineering
PhD in Diagnostic Microbiology, Faculty of Medicine
Reader in Biomedical Electronics, Faculty of Engineering
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