Potential of metabolomics in preclinical and clinical drug development

Pharmacological Reports 66 (2014) 956–963

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Pharmacological Reports journal homepage: www.elsevier.com/locate/pharep

Review article

Potential of metabolomics in preclinical and clinical drug development Baldeep Kumar, Ajay Prakash, Rakesh Kumar Ruhela, Bikash Medhi * Department of Pharmacology, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India

A R T I C L E I N F O

Article history: Received 1 March 2014 Received in revised form 3 June 2014 Accepted 10 June 2014 Available online 24 June 2014 Keywords: Drug Metabolomics Metabolism Toxicology Pharmacology

A B S T R A C T

Metabolomics is an upcoming technology system which involves detailed experimental analysis of metabolic profiles. Due to its diverse applications in preclinical and clinical research, it became an useful tool for the drug discovery and drug development process. This review covers the brief outline about the instrumentation and interpretation of metabolic profiles. The applications of metabolomics have a considerable scope in the pharmaceutical industry, almost at each step from drug discovery to clinical development. These include finding drug target, potential safety and efficacy biomarkers and mechanisms of drug action, the validation of preclinical experimental models against human disease profiles, and the discovery of clinical safety and efficacy biomarkers. As we all know, nowadays the drug discovery and development process is a very expensive, and risky business. Failures at any stage of drug discovery and development process cost millions of dollars to the companies. Some of these failures or the associated risks could be prevented or minimized if there were better ways of drug screening, drug toxicity profiling and monitoring adverse drug reactions. Metabolomics potentially offers an effective route to address all the issues associated with the drug discovery and development. ß 2014 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Analytical technologies used for metabolomics studies. . . Applications in preclinical and clinical drug development Biomarker discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Metabolomics in therapeutic target identification . . . . . . . Drug metabolism profiling . . . . . . . . . . . . . . . . . . . . . . . . . Metabolomics in drug development . . . . . . . . . . . . . . . . . . Drug toxicity profiling and ADR monitoring. . . . . . . . . . . . Metabolomics in neonatology . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abbreviations: ADR, adverse drug reaction; ALS, amyotrophic lateral sclerosis; COMET, Consortium for Metabonomic Toxicology; FTIR, Fourier transform infrared; GC, gas chromatography; H-D, hydrogen-deuterium; HMDB, Human Metabolomic Database; HPLC, high pressure liquid chromatography; IEMs, inborn errors of metabolism; MS, mass spectrometry; NMR, nuclear magnetic resonance; PCA, principal component analysis; PD, Parkinson’s disease; PLS-DA, partial least squares discriminant analysis; TMAO, trimethyl-amine N-oxide. * Corresponding author. E-mail address: [email protected] (B. Medhi). http://dx.doi.org/10.1016/j.pharep.2014.06.010 1734-1140/ß 2014 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

B. Kumar et al. / Pharmacological Reports 66 (2014) 956–963

Introduction From the last 20 years, the drug discovery and development process has become more and more expensive as well as risky. The ‘old’ testing or screening methods often fail to identify many false molecules at the early stage of drug discovery. There is a need for the development of new methodologies which will help in better understanding of altered genetic expression and cellular changes as metabolic markers and link these to the altering pathophysiology [1–3]. Metabolite can be defined as a substance (<1500 Da) produced from the chemical changes of either food or medication by the body. Some examples of metabolites include peptides, oligonucleotides, sugars, nucleosides, organic acids, etc. Metabolome can be defined as the quantitative collection of all the low molecular weight molecules (metabolites) present in cells in a particular physiological state and thus reflecting the cell’s status at that time. Metabolomics came into picture after the serial success of omics, i.e. genomics, transcriptomics and proteomics (Fig. 1). It is comparatively more precise and gives more informative data about the small metabolic molecules synthesized by the organism. Metabolomics approach was first originated at Imperial College London and has been used in disease diagnosis and toxicological studies [4]. Metabolomics helps in studying the treasury of endogenous small molecules present in organism. It is a complete analysis of the metabolome under a given set of conditions [5]. It is the only useful tool which tells us about the interactions between the genome, proteome and the external environment and provides the information about the sum total of all metabolic processes including anabolism and catabolism, and the related cellular processes such as absorption, distribution, and detoxification, signal transduction and regulation. It gives a direct picture of the cell’s activity and its surrounding environment status in various conditions reflecting health, disease and the effects of drugs and the environment factors [5]. Metabolomics can be defined as the quantitative assessment of the metabolic responses of a biological system (cell, tissue, organ or biological fluids) at a particular time and to measure the changes in the metabolic response when exposed to any pathophysiological stimuli and/or genetic alterations. It is an emerging and rapidly evolving science and technology system of comprehensive experimental analysis of metabolic profiles for diverse applications in disease diagnosis, toxicology, disease progression and genetic modification of specific organisms, drug discovery and development and clinical practice [6–10]. Studying the effects (therapeutic or adverse effects) of drugs or disease progression on whole organisms by metabolomics relies on multiparametric quantification of metabolic alterations over time in response to a drug or stressor [2]. Currently, the medical researchers are focusing on studying the biochemical, cellular and molecular alterations in the body in response to any disease or environmental stimuli. This could be helpful in

Fig. 1. Various ‘Omics’ and their interaction.

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developing the customized approaches for diagnosis as well as treatment. Metabolic profiling has offered a boost in the field of toxicology and drug development. It gives the more rapid and reproducible information about the drug metabolism and toxicity in preclinical and clinical development phases as compared to traditional methods. If we look at the technologies used for studying the metabolome, various high throughput techniques/methods are being used for detection and quantification of the small molecule metabolites present in an organism. Its unique focus on small molecules and the physiological effects of drugs on these small molecules aligns the field of metabolomics towards the interests of many pharmaceutical researchers. Metabolomics requires the correlation of the chemical information with both biochemical and physiological consequences in order to achieve the specific objectives [11]. Over the last decade, the field of metabolomics has rapidly growing with potential applications such as pathophysiology, disease diagnosis, functional genomics, pharmacology, toxicology, foods and nutrition. Many studies have already reported the metabolic profiles of several diseases including type 2 diabetes, hypertension, pre-eclampsia, hepatic pathologies, prostate and colon cancer, Huntington’s disease, motor neuron disease and depression [12]. Analytical technologies used for metabolomics studies Metabolomic studies consists of two sequential phases: (1) an analytical technique that is designed to study the full profile of low molecular weight metabolites in a biological sample to generate an all-inclusive spectrum; (2) followed by data analysis and interpretation [13]. Metabolomics crucially depends on analytical technologies in order to identify, quantify and characterize the small molecules/ metabolites in cell and organism. The principal techniques used for identification and characterization of metabolic profiling are nuclear magnetic resonance (NMR) spectroscopy and high resolution mass spectrometry (MS). Particularly, 1H NMR spectroscopy is widely used technique for the identification and characterization of metabolites in biological fluids such as plasma and urine [2]. NMR is useful for detection of the molecules in low concentrations (lower limit of detection 1 mmol/L). It allows the identification of compounds through the comparative analysis of chemical shifts or J-coupling patterns. Unlike mass spectrometry, this technique (NMR) does not require prior separation or chemical derivatization of components, to analyze the complex mixtures [14]. Afterwards, mass spectrometry is a highly sensitive technique (lower limit of detection <1 pmol/L) used for the identification and quantification of small molecules on the basis of their molecular weight, fragmentation patterns and chromatographic retention times [15]. MS requires a prior separation of the metabolic components in case of complex mixtures using either gas chromatography (GC) or liquid chromatography (LC). Currently, different techniques (for separation and identification) are used in combination for better resolution, such as LC–MS and GC–MS. The combination of other instrumental techniques such as LC–MSNMR has become widely useful for separation, dramatization and characterization of small molecules/metabolites. For the improvement of structural analysis and better interpretation of tandem mass spectroscopy (MS/MS) fragmentation data, Hydrogen-deuterium (H-D) exchange methods can be used in combination with MS [5,16]. Other techniques used for metabolomic analysis include Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy or electrochemical array detection [17]. Most of the detection

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Table 1 Various analytical technologies used for metabolic profiling. Type

Methods/techniques

References

Separation techniques

Gas chromatography (GC) Capillary electrophoresis (CE) High performance liquid chromatography (HPLC) Ultra performance liquid chromatography (UPLC)

Cesare et al. 2012 [18] Nicholson et al. [4] Rozen et al. [19] Tolstikov et al. [20]

Detection techniques

Nuclear magnetic resonance spectroscopy (NMR) Mass spectrometry (MS)

Odunsi et al. [21] and Sun et al. [22] Tea et al. [23] and Wei et al. [14]

Combination of techniques

GC–MS HPLC–MS

Liu et al. [16] and Sabatine et al. [24] Sun et al. [22] and Williams et al. [25]

GC–MS: gas chromatography–mass spectrometry; HPLC–MS: high performance liquid chromatography–mass spectrometry.

techniques require prior separation of the metabolic components found in the biological fluids or tissues. For the separation of these metabolic components from the biofluids, various separation techniques (Table 1) are used such as gas chromatography (GC), liquid chromatography (LC), high-pressure liquid chromatography (HPLC), ultra-HPLC or capillary electrophoresis [15]. Generally, the choice of analytical instrumentation and software depends on types of metabolites to be analyzed. For example, the identification of metabolic signatures in amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) has been achieved by using liquid chromatography followed by coulometric array detection [19,26]. Liquid chromatography with mass spectroscopy (LC–MS) is very sensitive technique that can be used for the identification, characterization and quantification of different compounds in a biological sample to obtain the best possible metabolic profile with regard to disease pathophysiology [20,27]. Most of the metabolomic data is recorded in the form of unassigned peaks of different intensity on different retention times (in case of chromatographic data), masses or mass fragments (mass spectrometric data) or chemical shifts (NMR data). The identification of compounds on the basis of these peaks or the interpretation of metabolomic data is the major challenge for the researchers involved in metabolomics. Two distinct approaches are available for interpretation of metabolomic data: untargeted and targeted metabolomics. Untargeted metabolomics is the complete analysis of all the metabolic molecules present in a sample, including unknown compounds. This approach is often coupled with advanced chemometric techniques (multivariate analysis) [28]. The disadvantages of this approach are: the time required to process huge amounts of raw data and the obstacles in identification and characterization of unknown small molecules. The targeted metabolomics is the quantitative approach for the characterization of a set of known metabolites. This approach is based on the spectral fitting and prior knowledge about the chemical or spectral properties of the metabolites of interest [29]. The identification of metabolites was initially undertaken on the basis of available databases and internal standards. The resulting data obtained can be used for pathway analysis or as input variables for statistical analysis. Though the metabolomics has an enormous potential in almost all fields of medical and pharmaceutical research such as oncology, pharmacology, medical biotechnology, biochemical analysis, etc., in this review, we are focussing towards the applications of metabolomics in preclinical and clinical pharmacological research which might be related to biomarkers discovery for diagnosis as well as drug efficacy studies, identification of new therapeutic targets, drug toxicity profiling and its application in neonatology.

clinical development and even beyond. Metabolomics can be used for lead selection, lead optimization, early in vivo toxicological testing, and in vivo efficacy screening. Other applications of metabolomics include preclinical biomarker identification, disease mechanism and validation of animal models for disease, and the discovery of biomarkers for evaluating the clinical safety and efficacy (Fig. 2). Advanced techniques involving the use of metabolic profiling can speed up the process of drug discovery and development by early identification and elimination of false candidates and improving the safety of new drugs [30]. Biomarker discovery The fundamentals of drug discovery are based on the extent of detection, measurement or monitoring of the target disease. For the development of a drug, the extent of disease (in terms of biomarkers) should be measurable. Interestingly, >80% of the diagnostic tests are based on the detection and measurement of small molecule metabolites as indicators of the disease (i.e. biomarker) [31]. A biomarker can be defined as a measurable characteristic that reflects the status of normal or pathogenic processes [32,33]. Metabolomics is primarily focused on identification, characterization and quantification of these small molecule metabolites in normal and abnormal physiological conditions. Identification and analysis of metabolites is very useful and precise tool for developing the biomarkers for disease diagnosis and drug therapy. These biomarkers tell us about the extent of disease progression (underlying mechanism) as well as effect of the drug molecules on disease progression and also on other small endogenous molecules [34]. Metabolomics approaches can be useful in detection of biomarkers in any biological sample such as serum, CSF, urine, saliva, and faeces [12,26,32,35]. Metabolomics provides rapid and non-invasive methods for identification of disease biomarkers. Metabolomics has already been used for the identification of small molecule metabolites for the diagnosis of several cardiovascular

Applications in preclinical and clinical drug development Metabolomics have a potential role in the pharmaceutical research and development (R&D), starting from drug discovery to

Fig. 2. Applications of metabolomics in nonclinical and clinical drug development.

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diseases such as high blood pressure [36], cardiac failure [37], coronary heart disease [38], Alzheimer’s disease [39], Parkinson’s disease [26], schizophrenia [40], ovarian and breast cancer [21,41]. According to Human Metabolome Database (HMDB), many small molecules biomarkers have been recognized which are found to be associated with more than 400 different disease conditions [42]. Metabolomics is the key to find universal biomarkers for diagnosis of disease and for the evaluation of drug efficacy. In a prospective study, the serum metabolic profiling of subjects with Alzheimer’s disease have shown altered levels of various metabolic biomarker signatures such as lipid metabolites, plasmalogens, sphingomyelins and sterols which was predictive of progression of Alzheimer’s disease. These findings indicate the role of oxidative stress as well as altered lipid metabolism in progression of Alzheimer’s disease [43]. In a cohort study, approximately 500 metabolites have been identified in the exercise induced myocardial injury. They have found a marked decrease in plasma levels of GABA in the subjects while no change was observed in controls [24]. In addition, the overexpression of the compounds of the citric acid pathway has been found in the metabolites which specifically changed in myocardial ischaemia. Previous reports have been also shown a fall in intermediates of citric acid cycle in the acute conditions of myocardial ischaemia in order to defend ATP production. Notably, the presence of intermediates such as succinate and a-ketoglutarate in blood have unexpected signalling effects by acting as ligands for orphan G protein-coupled receptor [44]. As metabolic profiling reflect the genetic and environmental interactions in patients, it may provide basis for the assessment of metabolism status of cardiac tissue at the time of surgery which could help to determine the susceptibility of cardiac muscles in order to identify the patients at risk of developing the complications. Hence, metabolomics may predict the connection between metabolites and disease condition. This can be helpful in early diagnosis and monitoring of therapeutic response in patients [45]. Metabolites can serve not only as biomarkers for disease progression but also as bio-markers of drug efficacy, i.e. they allow the rapid screening of new drug leads in animal models as well as in-vitro assays [46]. The exact pattern of metabolite concentrations found in humans may differ from that found in animals, but in many cases the general trends are preserved. For example, the effects of chloroethylnitrosourea on murine tumour models were recently investigated using metabolomics technology. In this study, they have found a significant accumulation of glucose, glutamine and aspartic acid in all tumours after the administration of chloroethylnitrosourea which corresponds to a suppression of de novo nucleoside synthesis pathway. In other words, we can say that these metabolites could be served as biomarkers of the efficacy of this anticancer drug [47]. National Cancer Institute, basic scientists, clinicians and industry are already on a way to expand the use of metabolomics for the assessment of therapeutic efficacy of drugs [48]. The intermediates of choline phospholipid metabolism have been proposed to be a possible biomarker for evaluation and monitoring of the therapeutic efficacy of various anticancer drugs [49]. Current examples of using metabolomics in development of anticancer drugs are tyrosine kinase inhibitors, heat shock protein inhibitors and proapoptotic agents [33,50–55]. Metabolomics in therapeutic target identification There is an urgent need of discovering newer therapeutic targets of diseases in order to develop new drugs. It also emphasizes that the diseases of today’s interest (obesity, cardiovascular disorders, cancer, neurodegenerative diseases) are multifaceted that are difficult to target with simple techniques [11]. The drug targets for these complex diseases can be explored

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with the help of metabolomics approaches. With the help of metabolomics, the novel targets for cancer chemotherapy has been discovered, for example, N-methylglycine in prostate cancer and 2hydroxyglutarate in AML [56]. The detailed understanding of the mechanisms involved in metabolism and energy production in cancer cells can be helpful on designing new drug molecules [57]. Many in-born errors of metabolism and other disorders such as diabetes, obesity and hypercholesterolemia, are often characterized by altered levels of metabolites. As in case of many metabolic disorders, low tyrosine levels in phenylketonuria, high levels of cystine and lysine in cystinuria and observed high levels of glutamine in cachexia, these metabolites act as markers of the respective disorders. Some of these metabolites may also serve as potential drug targets for the discovery and development of new drugs. Metabolic profiling or metabolomics may be helpful in identification of new disease targets and in better therapeutic moieties for these targets. In other words, metabolomics helps in target based drug discovery approach [29]. Drug metabolism profiling The absorption, distribution, metabolism, excretion and toxicology of drugs (ADMET), is one of the most important and time consuming process for drug development. ADMET is concerned with identifying the lead molecules which are potentially harmful, so that we can exclude them at the earliest stages of drug development process. Due to complex structures of new chemical entities, it is essential to predict their complete ADMET profile and concerned pathways involved for its further development [58]. ADMET studies are carried out in both preclinical and clinical stages of development. In the preclinical stage, ADMET testing involves collection of drug biotransformation data from in vitro assays, performing in vivo animal studies and collecting detailed histopathological and toxicological data [59], while in the clinical phase, the biochemical studies of blood, urine and faeces are performed [5]. The traditional methods for ADMET studies are invasive, expensive, prone to error and time consuming. There is a need of simpler, less invasive, quicker methods for ADMET studies. Recently, metabolomics has become one of the major contributors in the drug discovery and development process, helping in optimization of ADMET properties [29]. In particular, the introduction of high-throughput metabolomic screening methods has explored the new vistas for ADME monitoring and identification of metabolic pathways associated with drug metabolism [6]. These advanced metabolomic methods provide a more accurate and detailed picture of what is really happening inside the body in a very short period of time. The applications of metabolomics are widely used by pharmaceutical industries for performing the ADMET studies. Also, the FDA is planning to make this metabolomics studies as an integral part of new drug applications [29]. Metabolomics in drug development Drug discovery and development is an expensive, slow and risky business for the pharmaceutical industries. Only 6 out of 200 validated lead molecules reaches Phase I clinical trials and only one in six drugs progresses to Phase IV [60]. Even after reaching the marketplace, there is still a risk (5%) of drug withdrawn from the market because of adverse drug reactions [61]. These failures could be reduced or stopped by using better methods for drug target screening, tracking drug toxicity (at early developmental stage) and ADR (adverse drug reaction) monitoring. These risks can be prevented through a newly emerging field called metabolomics. With the emergence of metabolomics, the drugs which are likely to be fail in late clinical development due to toxicity, can be easily

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identified at the preclinical development stages of toxicology and ADMET profiling [58]. Half of small molecule drugs (approved by US FDA) are derived from pre-existing metabolites or natural products. Well known examples include corticosteroids and their derivatives (obtained from various plant and animal sources), ascorbic acid (from citrus fruits), salicylate (from willow bark), quinine (from cinchona bark), paclitaxel (from yew bark) and vincristine to treat non-Hodgkin’s lymphoma, antibiotics, anti-fungal and antiviral drugs [62]. Metabolomics can be useful to study the functional consequences of genetic and environmental variations which further helps in building and validation of new disease models for evaluating the efficacy [63,64]. With the incorporation of metabolomics, the time for clinical development can be shortened in order to make quicker availability of the drugs in market. Metabolomics can help in designing the clinical trials by selecting or targeting the specific subsets of patient population [29,65]. Drug toxicity profiling and ADR monitoring Not all the drugs are completely safe. There is always a balance between its safety and efficacy in order to make it available to patient population (market place). Many of these drugs (e.g. cancer chemotherapeutics) must be taken carefully to avoid drug interactions or the harmful toxic effects. There is a huge variation in drug interactions amongst individuals (depending on their age, gender and genotype) and also the doses that are found to be safe in one individual, may be lethal for another. So there is need to monitor serum levels and urinary clearance of drugs and drug metabolites in individual patients. Metabolomics has a greatest potential in toxicology (especially preclinical toxicity studies). Metabolomics potentially offers an inexpensive and convenient tool to monitor drug dosage and drug clearance in patients and also to track drug toxicity, adverse drug reactions [66,67]. The levels of drugs and drug metabolites can be detected using standard instrumentation technologies (such as NMR or MS) and metabolomic analysis. Drug toxicity investigation is one of major field which is impacted by the metabolomics. There is a strong need of developing new biomarkers of toxicity in the preclinical as well as clinical development of new drugs [68–70]. Metabolomics offers a balancing approach that provides the information about the changes in the functional integrity of the organism after drug administration. With the implementation of metabolomics, there is possibility to add up the more accurate information about the physiology and metabolism in drug toxicity studies. Initially, NMR was the major analytical tool for metabolomics studies as it is highly quantitative and reproducible in nature but later on more sensitive and reproducible techniques were used such as LC–MS or GC–MS [22,68,71]. Tissue specific biomarkers can be identified by characteristic changes in the levels and pattern of endogenous metabolites in biofluids/target tissue during toxicity. With the help of metabolomic approaches, it is now easier to perform toxicity studies such as identification of target organ of toxicity, identifying various possible mechanisms involved in toxicity, identification of biomarkers for measurement of toxicity, monitoring toxicity profiles and toxicokinetics [10]. Many of the toxicological findings arose from a joint effort between five pharmaceutical companies and the Imperial College London, called the Consortium for Metabonomic Toxicology (COMET). The main objectives of this project were to develop [1H] NMR based metabolomic database for performing various in vivo toxicological assays on drugs. With this joint effort, a database of 35,000 NMR spectra along with histopathology data on rodents for about 147 model toxins has been created [72]. On the basis of this database, various statistical/chemometric software were

developed for organ toxicity prediction which further helps in identification of organ (e.g. liver or kidney) specific toxins [11]. Many other studies have also explored a diversity of metabolite signatures for evaluating acute organ toxicity by employing NMR or LC–MS based analytical methodologies. In one such study of Dserine induced nephrotoxicity, the levels of lactate and amino acids-phenylalanine, tryptophan, tyrosine, valine was found to be elevated in urine [25]. While in another study, gentamicin induced renal toxicity was found to be associated with elevated levels of glucose and reduced levels of trimethyl-amine N-oxide (TMAO), xanthurenic acid and kynurenic acid in urine [73]. Metabolomics in conjunction with toxicogenomics reveals the mechanism responsible for the liver damage induced by the administration of high doses of pentamethyl-6-chromanol (PMCol), an anticancer drug. The mechanisms responsible for this damage has been found to be inhibition of glutathione synthesis and altered drug metabolism pathways [74]. Currently, metabolomics approaches are used by a number of pharmaceutical industries as a potential tool for safety and efficacy screening of drugs. It is used to identify the novel biomarkers for toxicity studies. Various novel biomarkers based on metabolomics have already been found for prediction of druginduced vascular injury and peroxisome proliferation [75,76]. NMR analysis of biofluids in various rodent models led to the finding of novel metabolic biomarkers of organ-specific drug toxicity. Drug induced renal papillary damage is found to be associated with altered levels of dimethylamine, trimethylamineN-oxide, N,N-dimethylglycine and succinate in urine [77]. The NMR spectrum of a biofluid provides a series of spectral regions that contain information about the metabolites associated with organ specific toxicity [1,78]. Metabolomics in neonatology A lot of efforts are required in the field of neonatology as only little is known about the overall metabolic status of the term and preterm neonate. There is a need of more understanding about the metabolic and development processes of neonates which can be further useful in improvement of their clinical management. The inter-individual variation in response to drug efficacy and toxicity is particularly affected by the biochemical and metabolic state of patients as a result of the interaction of both genetic and environmental factors [79]. Various individual factors such as gestational age, birth weight, post-natal age, nutritional status, the gut microbiota, hepatic and renal development can significantly alter the pharmacokinetic as well as pharmacodynamics of drugs in neonates. This leads to inaccurate drug prescribing and increased risk of drug toxicity in neonates [13]. Metabolomics has a potential application in studying the several perinatal and postnatal pathologies. Using this metabolomics approach, various clinical studies have been conducted in neonates and children (Table 2) in order to explore the different pathological conditions in neonates [80].

Table 2 Applications of metabolomics in neonatology. Areas of application

References

Gestational age, postnatal age Perinatal asphyxia Intrauterine growth retardation Prenatal inflammation and brain injury Respiratory diseases Cardiovascular diseases Renal diseases/injuries Metabolic diseases Nutritional studies on maternal milk and formula Pharma-metabolomics (pharmacometabolomics)

[81–84] [85–88] [23,89–92] [93] [94–96] [97–99] [100–103] [104,105] [18] [13,106,107]

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Metabolomics also act as an useful tool in the clinical management of neonates and infants. Urine is a widely used biological fluid in metabolomic studies reflecting the overall metabolic status of an individual. In this population, the most useful method of generating diagnostic information is the metabolomic analysis of urine sample which can be easily accessible with non-invasive procedures. In recent studies, various potential applications of metabolomics have been reported in neonatology. These studies have been focused on the important aspects of neonatal pathologies including gestational age related metabolic development, perinatal asphyxia, inborn errors of metabolism (IEMs), intrauterine growth retardation (IUGR), respiratory distress syndrome, renal diseases and effects of drug treatment [13]. Newborn piglets undergoing hypoxia-reoxygenation has been studied using 1H NMR based metabolomic analysis of urine in order to see the urinary metabolic changes as a result of hypoxic insult [108]. The changes in the principal metabolites (urea, creatinine, malonate, methylguanidine and hydroxyisobutyric acid) have been found in the piglets with hypoxic insult and in piglets resuscitated with different oxygen concentrations [108,109]. A recent metabolomics analysis of urine has shown the gestational age related differences in metabolic profiles of phenylalanine and tryptophan biosynthesis, urea cycle, tyrosine metabolism, arginine and proline metabolism [82]. The differences in neonates with IUGR and normal controls have been found in urinary metabolic profiles of myo-inositol, sarcosine and creatinine [90]. Recently, a metabolomic analysis of urine has shown to identify the children affected by nephrourological disorders. The development and function of renal system in neonates could be affected by metabolic changes (associated with other genetic factors) in prenatal and neonatal period. The maturation and development of nephrons is critically dependent on gestational age and intrauterine environment. The abnormal changes during gestational age may affect the metabolic status of newborns [80,100,109]. In clinical settings, only few metabolites can be measured in neonates using traditional methods. However, the application of metabolomic approach have revealed numerous metabolites (>2000) which can be useful in diagnosis of different metabolic disorders in a patient [80]. The implementation of metabolomics in neonatology may be useful in diagnosis of numerous disorders, identification of biomarkers as predictors of drug efficacy, monitoring drug-related toxicity, alterations in metabolic pathways and changes in the levels of metabolites after drug administration. Metabolomics appears to be a promising tool in neonatology. Other important applications of metabolomic analysis of urine in the newborn could be the monitoring of postnatal metabolic maturation, the identification of biomarkers of diseases and as early predictors of outcome, and monitoring of a personalized management of neonatal disorders [109]. Discussion Metabolomics is the powerful tool for exploring the alterations in the metabolic network which are involved in various pathophysiological conditions [11]. Metabolomics offers the platform for identification of genotype–phenotype as well as genotype–envirotype interactions. It is the only tool that provides the information about the connections between the genome, proteome and the external environment. Metabolomics is exclusively based on small molecules found in any living cell, organ or organism and the physiological effects of these small molecule metabolites. It gives the exact picture of the cellular activity and surrounding environment. Metabolomics allows for overall assessment of a cellular state within the immediate environment,

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i.e. genetic regulation, altered enzymatic activity and metabolic reactions [5,46]. Practically, it is impossible to cover the diversity of chemical compounds contained in human metabolome using a single analytical technique. NMR and mass spectroscopy are the most commonly employed analytical technologies for determination of detailed metabolic information. Currently, the combination of mass spectroscopy with chromatography (GC or LC) is widely used for the metabolic profiling. Major challenge for the researchers is the processing and interpretation of metabolic data. Two distinct approaches are used for processing and interpretation of metabolomic data obtained from the spectral analysis [15]. In the first approach (chemometric approach), the chemical compounds are identified by comparing their spectral patterns and intensities that distinguish sample classes [110]. While in chemonomic approach, the spectral patterns of sample is compared with the spectral patterns obtained from pure compounds [29]. Numerous studies have shown the correlation of single metabolite changes with the neonatal abnormalities which suggest their role as biomarkers of disease diagnosis and progression, but the knowledge on the overall metabolic state of low-weight neonates is still inadequate [90,91,111,112]. It is better to examine the entire metabolic profile determined by the interconnection of the different processes instead of taking one or few related metabolites into consideration [66,113]. Metabolomics appears to be a promising tool in neonatology with its important applications in the monitoring of postnatal metabolic maturation, the identification of biomarkers, diagnosis and monitoring of diseases and personalized management of neonatal disorders [80,114]. The use of modern testing methodology (such as metabolomics) can be helpful in accelerating the drug discovery and development process by detection of harmful candidate compounds at the earlier stages [30]. According to the available data in HMDB, the small molecule metabolites have been found to be associated with more than 400 different disease conditions. Metabolomics is most successfully used in diagnosis of various in-born errors of metabolism (IEMs) such as diabetes, obesity, etc. These metabolites or metabolic signatures allow rapid diagnosis of diseases as well as fast screening of new drug leads [31]. Most of the diagnostic tests rely upon measurement of these small molecule metabolites or biomarkers [15]. Metabolomics provides better tools for monitoring drug levels in patients and also to track toxicity associated with these drugs and adverse drug reaction (ADR) monitoring. It can also be used to identify drug–patient interactions [66]. Other applications of metabolomics include patient screening in clinical trial testing, post marketing surveillance, dosage monitoring and ADRs monitoring. It is playing a key role in drug discovery, development, clinical testing and approval. Conflict of interest statement None of the authors have any conflict of interest. Funding No funding source for this review article. References [1] Holmes E, Nicholson JK, Nicholls AW, Lindon JC, Connor SC, Polley S, et al. The identification of novel biomarkers of renal toxicity using automatic data reduction techniques and PCA of proton NMR spectra of urine. Chemom Intell Lab Syst 1998;44:251–61. [2] Nicholson JK, Lindon JC, Holmes E. ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 1999;29(11):1181–9.

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