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Professor of Analytical Chemistry, Department of Analytical Chemistry, Faculty of Chemical Technology, University of Pardubice, Czech Republic

Main research aims? Lipidomic analysis of biological samples using a combination of advanced mass spectrometric and chromatographic techniques with applications in the discovery and translation of cancer biomarkers for clinical screening.

Transforming disease diagnosis and treatment… I hope for improvements in high-throughput quantification of many biomolecules (lipids, metabolites, proteins, etc.), which will be correlated with the prediction and diagnosis of serious human diseases. The highest possible quality of analytical measurements and subsequent statistical evaluation of the data are prerequisites for such transformation because the mediocre quality of analytical data does not lead to the goal. I believe that physiological ranges of concentrations will be defined for particular subgroups (gender, age, BMI, ethnicity, etc.), so the outlying values will be used for the prediction, diagnosis, and treatment monitoring of many diseases using advanced statistical algorithms in combination with machine learning approaches and AI. However, the basis will always be the quality of the analytical measurements.

Missing from the analytical toolbox? We can generate enormous data sets with huge complexity, but then the data processing is starting to be a bottleneck. We have the instrumentation capable of generating such data sets, but we may have difficulties with the speed and quality of data processing. While reviewing manuscripts or reading articles already published in my field of lipidomics, I have observed frequent problems with identification, quantification, and data reporting. Some people are overwhelmed with the amount of data, which may result in a low quality of published papers even in the leading multidisciplinary journals. I recommend paying more attention to data processing and bioinformatics, which is far behind instrumental developments.