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16th International Conference on Metabolomics & Systems Biology, will be organized around the theme “Novel Trends in Metabolomics and Systems Biology During COVID-19”

Eurometabolomics-2020 is comprised of 21 tracks and 78 sessions designed to offer comprehensive sessions that address current issues in Eurometabolomics-2020.

Submit your abstract to any of the mentioned tracks. All related abstracts are accepted.

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Metabolomics is the systematic study of the metabolome, the unique biochemical fingerprint of all cellular processes. It is an Omics technology that allows simultaneous, global, and comprehensive characterization of small molecules in a biological system. It is the large-scale study of small molecules within a mass range of 50 – 1500 Daltons (Da), commonly known as metabolites, within cells, bio fluids, tissues or organisms. These metabolites within biological samples under given genetic, nutritional or environmental conditions are known as metabolome.

  • Track 1-1Metabolite identification and analysis
  • Track 1-2Metabolomics databases
  • Track 1-3Software workflow for metabolomics: Targeted and non targeted screening and validation
  • Track 1-4Metabolic network simulation

Systems biology is the study of biological systems at a cellular, molecular and organism level, as an integrated and interacting network of genes, proteins and biochemical reactions which give rise to life. It will become main stream in biological sciences this century. It can be used to systematically at all levels, from molecules to entire systems and its integration into quantitative models to gain knowledge in order to make accurate simulation of biological processes possible. The technologies such as genomics, bioinformatics, proteomics, mathematical and computational models are used for predicting dynamical behaviour and quantitative measurements of the behaviour.

  • Track 2-1Systems biology methods to characterize biological systems
  • Track 2-2Multicellular systems biology
  • Track 2-3Quantitative systems pharmacology
  • Track 2-4Mathematical biology
  • Track 2-5Pathways and networks
  • Track 2-6Modelling and simulation tools in systems biology

Metabolomics along with systems biology can be used to identify endogenous metabolites that modify protein expression. The main aim of Omics technologies is to reveal unexpected properties of biological systems by their nature. On behalf of metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with high sample numbers in reliable measurement times with respect to both technical accuracy and quantitation of small molecular weight metabolites. This prospective is a prerequisite for the analysis of dynamic systems. Accordingly, metabolomics is a key technology for systems biology.

 is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. In particular phases of synthetic biology workflow different types of  and metabolites, are useful.

  • Track 4-1Genome-scale modelling & flux balance analysis
  • Track 4-2In silico design of novel pathways
  • Track 4-3Signal transduction
  • Track 4-4Architecture of human metabolome
  • Track 4-5Computational data analysis in metabolomics
  • Track 4-6Metabolic flux analysis and metabolic models

Computational Biology is a rapidly emerging field, at the interface of computer science, arithmetic, physics and biology to study, analyse and understand complex biological systems by taking a corresponding integrated systems view using computational methodologies. The recent advances in computational methodologies are high throughput techniques and computational power. Computational systems biology provides a point of merging for genomics, proteomics, metabolomics and computational modelling and plays a key role in the fast progression of the evolving field by the outstanding developments in biology and computer science.

  • Track 5-1Machine learning and pattern recognition
  • Track 5-2Knowledge discovery and data mining techniques
  • Track 5-3Bioinformatics and cheminformatics
  • Track 5-4Sequence motifs and alignments
  • Track 5-5Hidden markov model
  • Track 5-6Sequencing algorithms
  • Track 5-7Stochastic modelling

Plant metabolomics is a recent research field that has gained increasing interest in the past few years and is applied for sub atomic level of the total metabolite and metabolome of plants under particular conditions. Metabolomics is applied for a better understanding the relation between genes and the biochemical composition of a plant tissue in response to its environment conditions and this information can be further used to assess gene function. The environmental metabolomics is use of metabolomics strategies to investigate the connections of life forms with their surroundings.

  • Track 6-1Metabolomics for exposomics
  • Track 6-2Metabolomics for exposomics
  • Track 6-3Toxicometabolomics
  • Track 6-4Microbiome-related metabolome
  • Track 6-5Environmental metabolome
  • Track 6-6Metabolomics of genetically modified crops
  • Track 6-7Nutrigenomics and plant functional genomics

Pharmacometabolomics/Pharmacometabonomics is used to determibe the metabolic biomarkers that could potentially predict different responses of clinical drugs by identifying differential metabolites at baseline and correlating their variations with the therapeutic outcomes. Presently, Pharmacometabolomics is still in its infancy because most pharmacometabolomics studies are merely focused on revealing the correlation between baseline metabotypes which are influenced by factors such as diets, ages, drug intake and gut microbiota with drug responses or disease susceptibility to study and minimize the metabolic biases.


NMR-based metabonomics categorises and provides information regarding organ-specific toxicity, monitor the onset and progression of toxicological effects, and identify biomarkers of toxicity. An upcoming challenge of metabolomics is to describe the cellular metabolome for purposes of understanding cellular functions. Such information is crucial if metabolomics is to provide a balancing dataset together with genomics and proteomics can be used to construct computer network models to describe cellular functions. NMR data are vastly reproducible and quantitative over a wide vigorous range and are unparalleled for determining structures of unknowns.


Diverse analytical techniques are needed to achieve higher coverage of metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing as a dynamic range in biological samples. The application of mass spectrometry in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques.

Metabolomics Analytical approaches for can be categorized largely into two discrete groups targeted or untargeted. These approaches can further be segmented as metabolic profiling, using an untargeted approach or metabolite identification and quantitation using a targeted approach. A diverse terminology for the definition of metabolic approaches has been used by various metabolomic research areas.

  • Track 10-1Targeted Metabolomics
  • Track 10-2Untargeted Metabolomics

The recent analytical platforms based on mass spectrometry and nuclear magnetic resonance has enabled separation, characterization, detection, and quantification of such chemically diverse structures. This continued development of these analytical platforms will accelerate extensive use and combination of metabolomics into systems biology

  • Metabolic Profiling: Metabolic profiling is defined as the identification and quantification of a selected number of pre-defined metabolites which are related to a specific metabolic pathway.
  • Metabolic Fingerprinting: Analysis of unbiased, rapid, global analysis of samples to provide sample classification is oriented towards defining clinically relevant differences rather than identifying all the molecules present in a sample. These metabolic fingerprints can be used to distinguish between different disease phenotypes and to predict a drug's effectiveness and toxicity.
  • Nuclear Magnetic Resonance: NMR-based metabonomics provides a means to categorize organ-specific toxicity, monitor the onset of action and progression of toxicological effects, and identify biomarkers of toxicity. It is used to describe the cellular metabolome for purposes of understanding cellular functions.
  • Mass Spectrometry: The application of mass spectrometry in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques.
  • Gas Chromatography-Mass Spectrometry
  • Liquid Chromatography-Mass Spectrometry
  • Capillary Electrophoresis-Mass Spectrometry
  • Fourier-Transform Mass Spectrometry: Among all the analytical platforms, which requires complementary analytical platforms for extensive coverage, atmospheric pressure ionization Fourier transform mass spectrometry (FT/MS) instruments are popular because they provide accurate mass measurements of ppm along with sub-ppm errors. It also high and ultra-high resolving power.
  • Track 11-1Metabolic profiling
  • Track 11-2Metabolic Fingerprinting
  • Track 11-3Nuclear magnetic resonance (NMR)
  • Track 11-4Gas chromatography–mass spectrometry (GC–MS)
  • Track 11-5Liquid chromatography–mass spectrometry (LC–MS)
  • Track 11-6Capillary Electrophoresis – Mass Spectrometry
  • Track 11-7Fourier-Transform Mass Spectrometry

Metabolomics is a recent area which potentials to contribute expressively to the characterization of various disease phenotypes and to the identification of personal metabolic features that can predict response to therapies and some of which are Microbiology, plants and medical science

  • Pharmacology & Pre-Clinical Drug Trials
  • Toxicology
  • Transplant Monitoring
  • New-Born Screening
  • Clinical Chemistry
  • Tool for Functional Genomics
  • Screening Services
  • Biomarker Search / Identification
  • Companion Diagnostics
  • Drug Development Optimization
  • LC/MS/MS Analysis
  • Combinatorics in Metabolomics
  • DATA Analysis & Interpretation

The application of metabolomics in the field of cancer research has led to the progress of metabolism in development of cancer. In the past ten years, the re-discovery of cancer as a metabolic disorder has happened due to the increased accessibility of metabolomics, identification of cancer metabolite biomarkers and the discovery of oncometabolites.

  • Biomarker in cancer diagnosis, prognosis, & therapeutic response Screening tool
  • Detection of micro metastases
  • As both predictive & pharmacodynamics marker of drug effect including search for new drugs
  • In Nutrigenomics it is used to see the effect of diet on cancer prevention and its response to treatment
  • As translational research tool which can provide link between clinical & laboratory
  • Molecular analyses of cancers to know the information about the mechanisms of initiation, progression & provide foundation for clinical tests
  • Track 13-1Cancer immunotherapy
  • Track 13-2Gene therapy
  • Track 13-3Targeted therapeutics
  • Track 13-4Novel approaches to cancer therapeutics
  • Track 13-5Active immunotherapies
  • Track 13-6Applications of metabolomics in oncology

Precision medicine is developing as a strategy to alter medical treatment to a small group or even discrete patients based on their genetics, environment and lifestyle. The increasing advance in metabolomics technology identifies the enormous potential of its application in personalized medicine. Merging metabolomics with genomics, transcriptomics, and proteomics studies will result in a significantly improved understanding of the disease mechanisms and the pathophysiology of the target clinical phenotype. The final goal of personalized medicine is to enable clinicians to prescribe the right medicine to the right patient at the right time with maximum efficacy and minimal toxicity.

  • Track 14-1Clinical applications of precision medicine
  • Track 14-2Precision medicine for mental disorders
  • Track 14-3Molecular biological profiling
  • Track 14-4Regenerative medicine and predictive medicine
  • Track 14-5Inborn errors of metabolism (IEM)
  • Track 14-6Nutraceuticals
  • Track 14-7Pharmacometabolomics and precision medicine

Over a period of time, metabolomics studies have identified several relevant biomarkers involved in complex clinical phenotypes using diverse biological systems. Metabolomics can be applied to identify biomarkers related to the perturbation being investigated and these biomarkers can be used to develop personalized prognostic, diagnostic, and treatment approaches. These discovered biomarkers can also be applied further in monitoring of disease progression, treatment efficacy, predisposition to drug-related side effects, and potential relapse.

  • Track 15-1Metabolite platform for validation of biomarkers
  • Track 15-2Biomarkers in drug development
  • Track 15-3Disease related biomarkers
  • Track 15-4Imaging biomarkers
  • Track 15-5Metabolomics in biomarker discovery

Metabolomics is being used in Drug Discovery and in development from lead compound discovery to post approval drug surveillance. Metabolomics can help in finding potential new sites for therapeutic intervention by identifying metabolic changes. Metabolomics can provide activity information about possible novel drugs and drug scaffolds, indicate interesting targets for drug development and suggest binding partners of compounds. Furthermore, metabolomics can be used for the discovery of novel natural products and in drug development. Metabolomics can enhance the discovery and testing of new drugs and provide insight into the on- and off-target effects of drugs.

  • Track 16-1Drug metabolism during drug design and development
  • Track 16-2Metabolites in identification of drug targets
  • Track 16-3Metabonomics in preclinical pharmaceutical discovery and development
  • Track 16-4Toxicology and drug metabolism
  • Track 16-5QSAR and ligand-receptor models
  • Track 16-6Applications in Drug Development

Chemotherapy drugs capable to cause significant, irreversible, life threatening organ damage which is distressing for patients and might affect the optimal delivery of treatment. Various studies have predicted the risk factors for drug induced organ damage because of lack of biomarker to pick-up these changes in early phase causes potential morbidity and mortality. Metabolomics can address relation between gene, drugs environment and thus increase our ability to predict individual variation in drug response phenotypes.

Nutritional metabolomics is rapidly developing small molecule chemical profiling to support integration of diet and nutrition in complex bio systems research. Foodomics is a new discipline that studies food and nutrition domains through the application of advanced Omics technologies which include the genomic, transcriptomic, proteomic, and metabolomics study of foods for compound profiling, authenticity, and biomarker detection related to food quality or safety, the development of new transgenic foods, food contaminants, and whole toxicity studies and the new investigations on food bioactivity, food effects on human health.

  • Track 18-1Food Metabolome
  • Track 18-2Food and Nutritional Metabolomics
  • Track 18-3Dietary metabolites and cellular metabolism
  • Track 18-4Food safety and contamination assessment using metabolomics
  • Track 18-5Applications of metabolomics to food processing

In field of pharmaceuticals, metabolomics is turning into an inevitably mainstream instrument for life sciences as it is generally fast and also precise procedure this can be connected with either a particular centre or in a international way to discover new learning about organic frameworks.

In paediatric medicine, the potential applications for metabolomics a highly informative technique that can also be used on non-invasively collected samples. NMR- based Metabolomics might serve as a promising approach for the diagnosis and prediction of mortality in septic shock in a paediatric population and that quantitative metabolomics methods can be applied in the clinical evaluations of paediatric septic shock.


Metabolomics is a novel approach that potentials to enable the detection of states of disease, to categories the patients based on biochemical profiles and to monitor disease progression. Metabolomic analysis may also be able to orient the choice of therapy, identify responders and predict toxicity, paving the way to a customized therapy.

  • Metabolomics in Neuropsychiatric Disorders: Metabolomics approach has revealed new opportunities in diagnostics of devastating disorders like neuropsychiatric disorders. Metabolomics-based technologies have the prospective to map early biochemical fluctuations in disease and hence provide a prospect to develop predictive biomarkers that can be used as indicators of pathological deviations prior to development of clinical symptoms of neuropsychiatric disorders.
  • Metabolomics in Metabolic Disorders: Metabolomics uses in the identification of metabolites not previously associated with metabolic traits highlight the importance and agitations of particular metabolites and advances novel strategies to prevent type 2 diabetes and illustrate biomarkers that can help with early detection, disease progression and therapeutic response. Consequently, the use of metabolomics in this area will continue to grow in basic research science and clinical medical applications.
  • Metabolomics in Cardiovascular Diseases: Cardiovascular diseases are the leading causes of death worldwide. There is a need for the development of particular diagnostic techniques, more effective therapeutic procedures as well as drugs, which can decrease the mortality rate in the course of CVDs. Metabolomic technologies may serve as diagnostic and/or prognostic tools that have the potential to significantly alter the management of CVD. Metabolomics can assist in the interpretation of perturbed metabolic processes, and improves our ability to understand the pathology of ischemic heart disease, atherosclerosis, and heart failure.
  • Metabolomic studies in Rheumatoid Arthritis: Metabolites from the nucleic acid and oxidative stress pathways are potential biomarkers for rheumatoid arthritis pathology. Metabolite profiles in rheumatoid arthritis plasma are associated to disease activity and treatment response. Metabolomic studies confirm the hypoxic nature of the inflamed synovial joint in rheumatoid arthritis.
  • Metabolomic studies in Systemic Lupus Erythematous: Low histidine levels have been identified in the serum of systemic lupus erythematosus (SLE) and RA could explain the increased incidence of cardiovascular disease observed for both rheumatic diseases. Taurine and citrate levels in the SLE urine metabolome have potential utility as biomarkers for SLE nephritis subtype discrimination.
  • studies in Ankylosing Spondylitis: Metabolite levels in serum reflect an alteration in the vitamin D3 metabolism in ankylosing spondylitis. Metabolomic studies of patients and controls identified reduced levels of tryptophan in ankylosing spondylitis, probably due to IFN-γ expression in the disease.
  • Metabolomic studies in Psoriatic Arthritis: To date, no studies have directly compared psoriatic arthritis and psoriasis metabolomics profiles. The urine metabolome in psoriatic arthritis is correlated with the changes in disease activity induced by anti-TNF treatment.
  • Metabolomic studies in Osteoarthritis: The prediction model built from the urine metabolite concentrations correlates significantly with the Kellgren–Lawrence radiographic scores of osteoarthritis severity. The valine/histidine and the xleucine(isoleucine and leucine)/histidine ratios are potential biomarkers of the development of knee osteoarthritis.
  • Metabolomic studies in Gouty Arthritis: Uric acid is not a sufficiently informative biomarker of gouty arthritis and additional markers must be identified. Gouty arthritis also expresses the common core of serum metabolites found in other prevalent arthritis. This common set of metabolites could be useful for the development of improved diagnostic systems.
  • Metabolomics in Nephrology: The application of metabolomics in nephrology research has expanded from the initial analyses of uraemia to include both cross-sectional and longitudinal studies of earlier stages of kidney disease. Chronic kidney disease, Diabetic nephropathy, Acute kidney injury, Kidney transplantation and End-stage renal disease
  • Track 21-1Metabolomics in Neuropsychiatric Disorders
  • Track 21-2Metabolomics in Metabolic Disorders
  • Track 21-3Metabolomics in Cardiovascular Diseases
  • Track 21-4Metabolomic studies in Rheumatoid Arthritis
  • Track 21-5Metabolomic studies in Systemic Lupus Erythematous
  • Track 21-6Metabolomic studies in Ankylosing Spondylitis
  • Track 21-7Metabolomic studies in Psoriatic Arthritis
  • Track 21-8Metabolomic studies in Osteoarthritis
  • Track 21-9Metabolomic studies in Gouty Arthritis
  • Track 21-10Metabolomics in Nephrology