Understanding genomic variation associated with AMR using AI and machine learning techniques
Drugs against diseases caused by viruses, bacteria and parasites have transformed human health and saved millions of lives. Nevertheless, their widespread use and misuse has led to the emergence of antimicrobial resistance that poses a potentially catastrophic threat to public health. The increasing power of genomic sequencing is offering new ways to rapidly detect and respond to the development of antimicrobial resistance. The availability of this wealth of data, along with the latest developments in artificial intelligence / machine learning (AI/ML) techniques, allows the development of sophisticated approaches that can fully leverage this data to pre-empt the effects of potential resistance mutations.
Our recent research will be presented into the development a robust and automated in silico framework to identify and understand the molecular consequences of single nucleotide polymorphisms that lead to therapeutic failure. Our findings from the study of a range of drug targets in M. tuberculosis (TB) and P. falciparum (Malaria) will be discussed. The use of such insights will be outlined in our on-going efforts to develop tools using ML/AI techniques that can help in the development of the next generation of drugs and in pathogen surveillance.
Dr Nick Furnham has expertise in computatioal biology, machine learning / AI, genomics and structural biology. He joined the School as an independent investigator supported by a MRC Strategic Skill Fellowship in Methodology Research. Prior to this he was a staff scientist / post-doctoral research in the group of Prof Dame Janet Thornton at the European Bioinformatics Institute (an outstation of the European Molecular Biology Laboratory).
He completed his PhD under the supervision of Prof Sir Tom Blundell in the Biochemistry Department at Cambridge University after a MSc in Bioinformatics at Exeter University. His original undergraduate training in Biological Science, where he specialised in parasitology, was at King鈥檚 College London.
This session will be live-streamed and recorded - accessible to both internal and external audience
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