Imperial College London


Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Research Associate (Chemometrician)



+44 (0)20 7594 3268caroline.sands01




Institute of Reproductive and Developmental BiologyHammersmith Campus





I am a postdoctoral research chemometrician at the MRC-NIHR Phenome Centre, a world-class facility for the metabolic phenotyping of human samples. Here, I contribute to quality-control assessment, method development and biomarker discovery and validation in patient- and population-based samples with the overarching aim of discovering robust diagnostic and prognostic markers for disease risk and personalized medicine. 

As such, my main research interests include: (1) elucidating the complex relationship between health status, diet, genetics, drugs, microbiome and environment in metabolic phenotyping based analysis of patients and populations (2) development of statistical methods for enhanced information recovery from spectroscopic data.

Research Interests

(1) Elucidating METABOLIC relationships

For example, investigating the microbial influences on metabolism.

Gut microbial metabolite associations

Gut microbial metabolite associations

(2) Development of Statistical Methods for Spectroscopic Data Analysis

For example, utilizing the inherent correlations between spectral variables in order to:

  • Identify, deconvolve and selectively remove drug metabolite signals from NMR data
  • Explore inter- and intra-metabolite connectivities 



Selected Publications

Sands CJ; Coen M; Ebbels TMD; Holmes E; Lindon JC; Nicholson JK. (2011). Data-Driven Approach for Metabolite Relationship Recovery in Biological 1H NMR Data Sets Using Iterative Statistical Total Correlation Spectroscopy. Analytical Chemistry. 83:2075-2082.

Sands CJ; Coen M; Maher AD; Ebbels TMD; Holmes E; Lindon JC; Nicholson JK. (2009). Statistical Total Correlation Spectroscopy Editing of 1H NMR Spectra of Biofluids: Application to Drug Metabolite Profile Identification and Enhanced Information Recovery. Analytical Chemistry. 81:6458-6466.



Sands C, Wolfer A, DS Correia G, et al., 2019, The nPYc-Toolbox, a Python module for the pre-processing, quality-control, and analysis of metabolic profiling datasets, Bioinformatics, Vol:35, ISSN:1367-4803, Pages:5359-5360

Wang X, Nijman R, Camuzeaux S, et al., 2019, Plasma lipid profiles discriminate bacterial from viral infection in febrile children, Scientific Reports, Vol:9, ISSN:2045-2322

Robinson O, Toledano MB, Sands C, et al., 2016, Global metabolic changes induced by plant-derived pyrrolizidine alkaloids following a human poisoning outbreak and in a mouse model, Toxicology Research, Vol:5, ISSN:2045-4538, Pages:1594-1603


Sands C, Wolfer AM, Sadawi N, 2018, phenomecentre/nPYc-Toolbox: nPYc, v.v1.2.1

Sands C, Wolfer AM, Correia G, et al., 2018, peakPantheR: Peak Picking and ANnoTation of High resolution Experiments in R, v.v1.2.3

More Publications