Real-time diagnosis and stratification of diseases

Deep molecular profiling of gene expression profiles to support clinical decision making in the management of cancer patients.

Gene expression profiling provides a detailed molecular snapshot of cellular phenotypes that can be used to compare different biological conditions. Nanopore sequencing technology is capable of generating high-resolution transcriptomic data in real-time and at low cost, which heralds new opportunities for molecular medicine. In this project, we are investigating the clinical utility of real-time transcriptome profiling by processing RNA sequencing data from pediatric patients on the fly using machine learning models. This strategy has proven successful at distinguishing between leukemia disease subtypes, which we are now seeking to translate into contemporary clinical workflows. We are now generating transcriptomic and epigenomic data for other diseases, where conventional clinical workflows are inexistant, inaccurate or require lengthy turnaround times.

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