Imperial College London

Dr Matthew R. Lewis

Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Director of Metabolic Profiling - COO NPC







660Sir Alexander Fleming BuildingSouth Kensington Campus





As head of the section of Bioanalytical Chemistry, I oversee a talented and diverse team of experts responsible for the development and application of novel analytical methodology for global profiling and targeted analysis of small molecules, peptides, and beyond. Our principal application space is human biofluids and tissue extracts as well as the animal models and cell cultures needed to explore disease mechanisms in greater depth. Our favoured technology platforms include nuclear magnetic resonance (NMR), liquid chromatography mass spectrometry (LC-MS) and LC-tandem mass spectrometry (LC-MS/MS). We are most active in the areas of:

  • Analytical method development
  • Technology development and refinement
  • Data extraction and pre-processing workflows
  • Data quality control and monitoring
  • Metabolite assignment and identification including structure elucidation

Together we work closely with clinicians, epidemiologists, and basic science researchers at Imperial to provide innovative and reliable solutions for metabolomics, lipidomics, and soon for proteomics.

As the Chief Operations Officer for the National Phenome Centre (NPC), I am responsible for operational management and delivery of a wide portfolio of research collaborations. Within the NPC, our focus is split between meeting the needs of high precision analysis demanded by large sample cohorts from molecular epidemiology studies, and those of studies involving smaller clinically derived cohorts analysed using both established and developing technologies.



Li J, 2021, Roux-en-Y Gastric bypass-induced bacterial perturbation contributes to altered host-bacterial co-metabolic phenotype, Microbiome, Vol:9, ISSN:2049-2618

Wolfer AM, Correia GDS, Sands CJ, et al., 2021, peakPantheR, an R package for large-scale targeted extraction and integration of annotated metabolic features in LC-MS profiling datasets., Bioinformatics

Maciejewski M, Sands C, Nair N, et al., 2021, Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics, Scientific Reports, Vol:11, ISSN:2045-2322

Takis PG, Jiménez B, Al-Saffar NMS, et al., 2021, A computationally lightweight algorithm for deriving reliable metabolite panel measurements from 1D 1H NMR., Analytical Chemistry, Vol:93, ISSN:0003-2700, Pages:4995-5000

Sands CJ, Gómez-Romero M, Correia G, et al., 2021, Representing the metabolome with high fidelity: range and response as quality control factors in LC-MS-based global profiling., Analytical Chemistry, Vol:93, ISSN:0003-2700, Pages:1924-1933

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