TRACK 1: Metabolomics

Metabolomics is the study of the metabolome/metabolites, 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.

•  Metabolomics, which is defined as the comprehensive analysis of metabolites in a biological specimen, is an emerging technology that holds promise to inform the practice of precision medicine.
• It is an analytical profiling technique for measuring and comparing large numbers of metabolites present in biological samples. Combining high-throughput analytical chemistry and multivariate data analysis, metabolomics offers a window on metabolic mechanisms.
• It is the global analysis of all or a large number of cellular metabolites. Like other functional genomics research, metabolomics generates large amounts of data. Handling, processing and analysis of this data is a clear challenge and requires specialized mathematical, statistical and bioinformatics tools.

TRACK 2: System metabolomics

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 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.

• Systems metabolomics combines a wide array of techniques to obtain detailed pictures of the dynamic state of metabolism. Routine clinical application requires appropriate proxy readouts designed upon identification of design principles.
• The primary aim of "omic" technologies is the non targeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample. By their nature, these technologies reveal unexpected properties of biological systems.
• Metabolomics is refined analysis of quantitative dynamics in biological systems. For 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 the identification and quantitation of small-molecular-weight metabolites.

TRACK 3: Metabolomics in Systems Biology

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

• Metabolomics is a key technology for systems biology. 
• The aim of this review is to provide an in-depth overview about metabolomics technology.
• And to explore how metabolomic networks can be connected to the underlying reaction pathway structure, and discuss the need to investigate integrative biochemical networks.

TRACK 4: Metabolic Modelling and Synthetic Biology

Synthetic biology main purpose is to create novel biological functions and systems by combining biology with engineering stream. The workflow of the development of novel biological functions with synthetic 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 differing types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful.

• Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering.
•  Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology.
• Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow.
• The role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory.

TRACK 5: Computational Methodologies

Computational Biology may be a rapidly emerging field, at the interface of physics, arithmetic, computing and biology to review, analyse and understand complex biological systems by taking corresponding integrated systems 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.

• Computational biology has become an important part of developing emerging technologies for the field of biology.
• It involves the development and application of data-analytical and theoretical methods, mathematical modelling and computational simulation techniques to the study of biological, ecological, behavioural, and social systems.
• Computational biology and bioinformatics is an interdisciplinary field that develops and applies computational methods to analyze large collections of biological data, such as genetic sequences, cell populations or protein samples, to make new predictions or discover new biology.
• It has been used to help sequence the human genome, create accurate models of the human brain, and assist in modeling biological systems.

TRACK 6: Plant and Environmental Metabolomics

Plant metabolomics may be a recent research field that has gained increasing interest within the past few years and is applied for sub atomic level of the entire 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.

• Changes in plant metabolism are at the heart of plant developmental processes, underpinning many of the ways in which plants respond to the environment. As such, the comprehensive study of plant metabolism, or metabolomics, is highly valuable in identifying phenotypic effects of abiotic and biotic stresses on plants.
• It can help us to obtain a better understanding of the complexity of the biological systems, through the chemical composition and relations with the physiology of the plant.
• The complex of physical and chemical events of photosynthesis, respiration, and the synthesis and degradation of organic compounds can be obtain by metabolomics.
• It  is an interesting approach that has been used in the plant sciences, especially in ecological studies, in investigating the effects of environmental factors on plant metabolism. Metabolomic profile data have been utilised to compare different species from the same family, or individuals from populations from the same species growing under different environmental conditions, or changes in metabolite production of individuals within the same population at different seasons.

TRACK 7: Pharmaco-metabolomics

Pharmaco-metabolomics used to determine 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, Pharmaco-metabolomics remains in its infancy because most pharmaco-metabolomics studies are merely focused on revealing the correlation between baseline metabotypes which are influenced by factors like-gut, ages, drug intake and diets microbiota with drug responses or disease susceptibility to review and decrease the metabolic bases.

• It uses metabolic phenotypes for the prediction of inter-individual variations in drug response and helps in understanding the mechanisms of drug action. The field has made significant progress over the last 14 years with numerous studies providing clinical evidence for personalised medicine.
•  Pharmacometabolomics can be applied to measure metabolite levels following the administration of a pharmaceutical compound, in order to monitor the effects of the compound on certain metabolic pathways(pharmacodynamics). 
• It helps in mapping of drug effects on metabolism and the pathways that are implicated in mechanism of variation of response to treatment.
•  This approach can then be applied to the prediction of response to a pharmaceutical compound by patients with a particular metabolic profile.

TRACK 8: NMR-based Metabolomics

NMR-based metabolomics provides information regarding organ-specific toxicity, monitor the onset and progression of toxicological effects, and recognize biomarkers of toxicity. An upcoming challenge of metabolomics is to explain the cellular metabolome for purposes of understanding cellular functions. Such information is crucial if metabolomics is to supply a balancing dataset alongside genomics and proteomics are often wont to construct network models to explain cellular functions. NMR data are vastly reproducible and quantitative over a wide vigorous range and are unparalleled for determining structures of unknowns.

•  It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens.
• It is nondestructive, nonbiased, easily quantifiable, requires little or no chromatographic separation, sample treatment, or chemical derivatization, and it permits the routine identification of novel compounds.
• Unlike most other metabolomic platforms, NMR is not restricted to biofluid or tissue extract analysis.
•  The correlation between two and even three different nuclei can be measured using multidimensional NMR methods.

TRACK 9: Mass Spectroscopy (Ms) based Metabolomics

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 home in biological samples. The application of mass spectrometry has increased exponentially since the discovery and innovation of electrospray ionization and matrix-assisted laser desorption ionization techniques.

• Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously.
• However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome.
• It also offers quantitative analyses with high selectivity and sensitivity and the potential to identify         metabolites.

TRACK 10: Approaches in Metabolomics

Metabolomics Analytical approaches 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 metabolomics research areas.

• Metabolomics is of keen interest to the broader community given its key position as a ‘real world endpoint’ in applications such as understanding plant metabolism, environmental stress and disease.
• The two most common analytical approaches for the generation of metabolomics data are nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). NMR is a spectroscopic technique based on the principle of energy absorption and re-emission of the atom nuclei due to variations in an external magnetic field.
• It can provide a better understanding of the state of cellular and biological processes at different stages of growth, under disease conditions, in response to stimuli, and even as a molecular signature for cell identification.

TRACK 11: Microbes in Human Metabolome

The human GIT is habitat for many microbes. Metabolomics was first adopted for clinical diagnosis by biochemical geneticists seeking to identify metabolic biomarkers for inborn errors of metabolism (IEM). These microbes employ unique strategies to gain energy in this largely anaerobic environment. The gut microbiota produces a broad range of metabolic products that accumulate to high levels in the gut. Metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases.

• Metabolomics research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest characterize small molecules produced by intestinal microbes, and define the biochemical pathways of metabolites.

 

TRACK 12: Metabolomics in various Diseases

Metabolomics is new omics platform that offers great potential for the diagnosis and prognosis of neurodegenerative diseases as an individual metabolome reflects alterations in genetic, transcript, and protein profiles and effects from the environment. Small numbers of metabolites have been used to diagnose complex metabolic diseases as well as monogenic disorders such as inborn errors of metabolism. Metabolic alterations in Cardiopulmonary Vascular Dysfunction are the leading purpose of death worldwide which is affecting the functions of the blood vessels and heart.

• Hypertension
• Obesity
• Cardiovascular disease
• Atherosclerosis

TRACK 13: Clinical Metabolomics

Clinical metabolomics is achieving appreciation as an essential tool in precision medicine. Significant progress in separation science, mass spectrometry, and nuclear magnetic resonance spectroscopy occurring within the past few years are responsible for strengthening the analytical basis for metabolite identification and measurements in clinical samples. Metabolomics plan in the modern clinical approaches will allow a generous of diseases mechanisms and pathophysiological conditions, as well as providing innovative tools for novel diagnostic and prognostic approaches. Decades of research have energetically recommended that metabolism is not a self-regulating network operating independently.

• Clinical metabolomics is emerging as a tool for IEM screening.
•  The goal of Metabolon’s approach to metabolomics in this setting is to measure the entire small molecule metabolite content of a patient sample with comparison to a control reference population to identify biochemical pathway disturbance.
• The application of clinical metabolomics to the identification of IEM (Inborn errors of metabolism).

TRACK 14: Nutritional Metabolomics

Nutritional metabolomics is using chemical profiling of tiny molecules to support the assimilation of nutrition and diet in complex bio-systems research. Nutrigenomics is a branch of nutritional genomics which deals with the effects of foods and food constituents on gene expression. Foodomics derived from the digestion and biotransformation of foods and their constituents during which MS techniques are considered indispensable. It has emerged with two major goals:

• To determine the effects of dietary compounds on host metabolism after consumption for a           defined period of time.
•  To identify dietary intake or phytochemical dose-dependent associated metabolite biomarkers.

TRACK 15: Genomics

Genomics uses a combination of recombinant DNA, DNA sequencing methods, and bioinformatics, to assemble, and analyse the structure and function of genomes. Thus, proteins structure body structures, for instance, organs and tissues and additionally control concoction responses and convey motions between cells. Genomics likewise includes the sequencing and examination of genomes through employments of high throughput DNA sequencing and bioinformatics to gather and break down the capacity and structure of whole genomes.

• Genomic approaches to understanding the mechanism of disease pathogenesis and its relationship to genetic factors, including meta-genomic and the mode and tempo of gene and genome sequence evolution.
• Using high-performance computing and math techniques known as bioinformatics, genomics researchers analyze enormous amounts of DNA-sequence data to find variations that affect health, disease or drug response.
• Genomic technology and methodology development, with a focus on new and exciting applications with potential for significant impact in the field and emerging technologies.

TRACK 16: Cancer genomics

Cancer genomics is the study of the entirety of DNA sequence and gene expression differences between tumour cells and normal host cells. It aims to understand the genetic basis of tumour cells its proliferation and the evolution of the cancer genome under mutation and selection by immune system, the body environment and therapeutic interventions.

• It aims to understand the genetic basis of tumour cell proliferation and the evolution of the cancer genome under mutation and selection by the body environment, the immune system and therapeutic interventions.
• The study of cancer genomes has revealed abnormalities in genes that drive the development and growth of many types of cancer.
• Cancer genomics will be applied in the future to clinical disease diagnosis and prognosis. 

TRACK 17: Protein Expression and Analysis

Protein expression refers to the way in which proteins are synthesized, modified or changed and regulated in living beings or organisms. Recombinant protein expression refers to the construct of proteins which derived from recombinant DNA. In protein research, protein expression can apply to either the object of study or the laboratory techniques required to manufacture proteins. Protein analysis is the bioinformatics study of protein structure, it’s interaction and function using database searches, sequence comparisons, structural and functional predictions.

• Proteins are synthesized and regulated depending upon the functional need in the cell. 
• In general, proteomics research involves investigating any aspect of a protein such as structure, function, modifications, localization or protein interactions. 
• The expression level of a gene can be by staining the protein or mRNA when it is still in the cell

TRACK 18: Metabolomics in field of Paediatric Medicine

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

• Helps in the optimization of individualized therapy and nutrition.
•  Assessing drug-related efficacy or toxicity.
• Identifying phenotype changes associated to disease onset and progression, improving early diagnosis and prognosis.

TRACK 19: Metabolomics in Metabolic Engineering

Metabolic engineering is the need of genetic engineering to modify the metabolism of an organism which deals with measurement of metabolic fluxes and elucidation of their control as determinants of cell physiology and metabolic function. An innovative aspect of metabolic engineering is that it evacuate from the outdated reductionist paradigm of cellular metabolism, taking a holistic view. Metabolic engineering is acceptable as a framework for the analysis of genome wide differential organic phenomenon data, together with data on protein content and in-vivo metabolic fluxes.

• The main aim of metabolic engineering is to manipulate metabolite production.
• Goal is to provide information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound.

TRACK 20: Lipidomics

Lipidomics is an increasing field with plentiful applications. ESI mass spectroscopy is used to investigate the different cell types. Identification of lipid composition and quantification of cellular lipids gives us details about the lipid related pathway which also helps in identification of metabolic pathways and the effected enzymes. The need for bioinformatics is to maintain and integrate the experimental data in various aspects, such as-database design, visual display, for lipid classification analysis, and ontologies and play diverse roles in human physiology.

• Obesity
•  Atherosclerosis
•  Stroke
• Hypertension
• Diabetes mellitus

TRACK 21: Approaches in Cancer Metabolomics

Cancer biomarkers have many potential applications in cancer diagnosis, including screening, diagnosis, risk assessment, prediction of response to treatment, and monitoring of progression of the disease. Metabolomics is growing within the field with particular attention to its application as a biomarker in cancer diagnosis. Biomarkers could incorporate a good scope of biochemical elements, for instance, differing types of lipids, enzymes, proteins, macromolecules, and tiny metabolites, sugars, cytogenetic parameters and cytokinetic etc.

• Cancer is a devastating disease that alters the metabolism of a cell and the surrounding milieu. Metabolomics is a growing and powerful technology capable of detecting hundreds to thousands of metabolites in tissues and biofluids.
• The global analysis of small molecule metabolites that like other -omics technologies can provide critical information about the cancer state that are otherwise not apparent

 

 

Growth and challenges of Change in Metabolomics Sector Propelling Market on a High Growth Trajectory

The Global Metabolomics Market is predicted to succeed in USD 2,386.4 million by 2021 from USD 1,209.4 million in 2016, at a CAGR of 14.6% during the forecast period. Metabolomics may be a powerful and unique analytical approach for the systematic identification and quantification of small-molecule metabolites, metabolite target analysis, metabolic profiling, and metabolic fingerprinting in various biological systems and samples. This metabolomics technology market majorly comprises detection techniques such as mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), and separation techniques such as gas chromatography. These techniques are utilized in metabolome studies, primarily in toxicology testing and developing personalized medicine.

Market Dynamics

Drivers

 • Availability of government and private funding

 • Increasing pharmaceutical and biotech R&D expenditure

 • Technological advancements

 • Growing demand for personalized medicine

 • Increasing use of metabolomics in toxicology testing

Restraints

• Issues related to data examination and processing

• High cost of tools and instruments

Opportunities

• Biomarker development

• Rapid growth opportunities in emerging markets

Challenges

• Complexity and diversity of biological samples

• Dearth of skilled researchers

Key Market Trend

A hyphenated technology is a combination of two or more analytical tools. Hyphenated technologies reduce cost by requiring the installation one instrument. They also provide ease of operation and require lesser space as compared to the installation of two or more standalone devices. In addition, these technologies have broadened the applications of analytical techniques within the analysis of biomaterials, especially natural products.

 

Scientists and Researchers organizers

Directors of Biochemistry department

Hospitals and Healthcare professionals

Metabolomics Research and Development (R&D) Companies

Metabolomics Instrumentation Technology Product Manufacturers

Metabolomics Industry Consulting Firms

Pharmaceutical companies

Genetics Associations and Societies

Doctors

Academic researchers

Professors

Business delegates

Young Researchers

Advertising and Promotion Agency Executives

Medical & Pharmaceutical Companies

Biomedical Research organizations, societies and associations

Software developing companies

Data Management Companies

Metabolomics is the quantitative and qualitative study of small molecules. It is said to be an important technique in systems biology. The purposes of metabolomics is accurate detection of disease, such as inflammation, necrosis, estimation of toxicity in newly designed drugs, Alzheimer’s, drug testing and interpreting biochemical pathways.  Greater than 95% of clinical diagnostic assays tests are for small molecules. From pre-existing metabolites, 50% of the drugs are derived from known small molecule drugs. 

 

Honorable scientific talks by the global scientific community

Sterling workshop sessions

Poster - paper presentations and world-class exhibitions

Opportunities to gain a deeper understanding of the topic

Meet Academics and Industrial professionals to get inspired

Great credits for the work in progress

Valuable talks and symposiums from renowned speakers

Meaningful sessions and accomplishments

Exquisite Platform for showcasing your products and International Sponsorship

Awards and Global Recognition to meritorious Researchers

Global Networking opportunities with 50+ Countries

https://www.metabolomicsconference.com/2019