SOMERVILLE MAGAZINE 9
Inside The NMR Revolution Since her appointment as Somerville’s inaugural Dorothy Hodgkin Fellow in 2020, Dr Fay Probert has seen her research garner national headlines and industry partnerships. She joins us to explain the revolutionary diagnostic power of combining AI dataset analysis with Nuclear Magnetic Resonance spectroscopy.
Photo: Jack Evans
specialism in metabolomics, the scientific study of chemical processes involving the small molecule substrates, intermediates and products of cell metabolism called metabolites.
I
n a sense, my whole career has been guided by the search for interdisciplinary collaboration. As a maths undergrad, the projects that most fascinated me involved using complex mathematical methods to understand biological processes like viral infection. This led me to do an MSc in mathematical biology and analytical chemistry. It was there I had my first encounter with Nuclear Magnetic Resonance (NMR) spectroscopy; I was completely blown away. NMR combines physics and chemistry to extraordinary effect, using purely quantum mechanical phenomena (an intrinsic property of the nucleus called ‘spin’) to provide structural and dynamic information about chemicals in exquisite detail. Following my first brush with NMR, I knew I had to do a PhD in that field – which led in turn to my current
NMR is highly versatile: it can determine molecular structures, test drug kinetics, even evaluate food safety. But the function we rely on is NMR’s capacity to analyse complex mixtures with just a single experiment. This means we take a small amount of blood or another biofluid and, in just a few minutes, create ‘biomarker constellations’ that tell us a huge amount of chemical information about the metabolites present in the sample. We then use machine-learning algorithms (many of which I write – calling on my aforementioned love of maths!) to pick out the metabolite signals that indicate specific conditions or disease progression. This multi-marker approach holds many advantages over traditional blood tests, which can only measure one marker at a time. An increase in one metabolite alone may not give sufficient accuracy for a diagnostic test, but an increase in metabolite ‘A’ coupled with a simultaneous decrease in metabolites ‘B’ and ‘C’ gives a holistic picture that vastly improves diagnostic accuracy.
Above: The Axinon System by numares AG, which Dr Probert uses to elucidate metabolite constellations
After MS and cancer, potential uses for multi-marker testing inciude Alzheimer’s and even depression.
