Utilising Quantum Machine Learning and quantum computing for genomic research and development

Quantum Base Alpha is working with the University of Edinburgh and the Medicines Discovery Catapult to utilise the potential of Quantum Computing (QC) together with Quantum Machine Learning (QML)to help the UK government department DHSC enhance medicine discovery. The project's focus is using advanced QML bioinformatics tools to study the genomics of pathogens.

Genomics can be thought of as the fragmentation, sequencing, and reassembly of DNA to generate a full computational representation of this DNA. It is a cornerstone of modern medicine and biological science and research. Genomics is a rapidly growing market segment and is essential in future drug discovery.

It has been shown statistically that DNA has many similarities to human languages and classic Machine Learning transformer models have given promising results in this field.

QBA will incorporate quantum computing into these classic machine learning approaches to study the pathogens and suggest ncDNA regions for drug development. This should provide a quantum advantage in fidelity, accuracy and computational cost.

Our intention is to create a quantum computational platform that supports the identification of disease-relevant functional regions within ncDNA sequences and develop applications against Disease X and future epidemics.