I am the Waters Senior Lecturer in Molecular Spectroscopy in the Department of Surgery and Cancer. I joined Imperial College in 2006 after working as a postdoctoral researcher at the Scripps Research Institute in La Jolla, CA. At Imperial College, I was initially a postdoctoral researcher for the Consortium for Metabonomic Toxicology (COMET) group.
My research focuses primarily on the development and application of novel mass spectrometry (MS) based techniques for metabolic phenotyping and on the fusion of mass spectrometric methods with chemometric analysis, which is currently a significant bottleneck in the analysis pipeline. Broadly, my research at Imperial College has involved the development, optimisation and application of UPLC-MS methodologies for the analysis of biological samples, largely in the context of metabolic phenotyping: serum, urine, tissue, amniotic fluid, and microdialysates. These developmental advances have resulted in shorter analysis times – and therefore higher sample throughput – key for large scale metabolic phenotyping studies. Peak detection and analytical reproducibility have been enhanced, improving metabolome coverage and the potential for biomarker identification and quantification.
I am applying these methods to biomedical research areas including toxicology, cardiovascular disease, neonatal disease and development, maternal exposures and effects on early childhood, and neurological diseases.
et al., Leptin and fractalkine: Novel subcutaneous cytokines in burn injury, Disease Models and Mechanisms, ISSN:1754-8403
et al., 2019, Microdialysis workflow for metabotyping superficial pathologies: application to burn injury, Analytical Chemistry, Vol:91, ISSN:0003-2700, Pages:6541-6548
et al., 2018, Efficacy of arginine depletion by ADI-PEG20 in an intracranial model of GBM, Cell Death and Disease, Vol:9, ISSN:2041-4889
et al., 2018, Determinants of the urinary and serum metabolome in children from six European populations, Bmc Medicine, Vol:16, ISSN:1741-7015
et al., 2018, Development of a novel UPLC-MS/MS-based platform to quantify amines, amino acids and methylarginines for applications in human disease phenotyping, Scientific Reports, Vol:8, ISSN:2045-2322