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Pharmaco-metabonomic phenotyping and personalized drug treatment
Abstract
There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.
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“Despite variability introduced by diet and comorbid conditions, metabolomic biomarkers such as reduced docosahexaenoic acid (DHA) and elevated homocysteine have demonstrated clinical utility133,194, 195, 196, 197, 198, 199.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [197]
In the citing paper
“Adult humans are characterized by individual metabolic phenotypes [37,38,39,40,41]; there are areas of the metabolome unique to each individual that remain stable over time. “Metabolic profiles” can be detected that allow us to predict which individuals may present ways of metabolizing drugs that make them more susceptible to presenting DILI [17].”
From Metabolomic Analysis of Pediatric Patients with Idiosyncratic Drug-Induced Liver Injury According to the Updated RUCAM (2023) · cites this paper as [37]
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BackgroundZhang, A., Sun, H. J., Wang, P., Han, Y., & Wang, X. (2011) · Complementary Therapies in Medicine · doi:10.1016/j.ctim.2011.10.007 · Cited by 121
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Self-citationDumas, M.-E., Rothwell, A. R., Hoyles, L., Aranias, T., Chilloux, J., Calderari, S., Noll, E. M., Péan, N., Boulangé, C. L., Blancher, C., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.06.039 · Cited by 114
“To evaluate microbial metabolites as prodromal markers, we repurposed a pharmaco-metabonomics framework (Clayton et al., 2006), which we developed initially for drug toxicity prediction using pre-dose metabolic phenotypes, to predict complex metabolic and behavior phenotype outcomes following HFD feeding in isogenic m…”
MethodSelf-citationParacetamol metabolism, hepatotoxicity, biomarkers and therapeutic interventions: a perspective
Athersuch, T. J., Antoine, D. J., Boobis, A. R., Coen, M., Daly, A. K., Possamai, L. A., Nicholson, J. K., & Wilson, I. D. (2018) · Toxicology Research · doi:10.1039/c7tx00340d · Cited by 125
Self-citationPhylometabonomic Patterns of Adaptation to High Fat Diet Feeding in Inbred Mice
Fearnside, J., Dumas, M., Rothwell, A. R., Wilder, S. P., Cloarec, O., Toye, A. A., Blancher, C., Holmes, E. C., Tatoud, R., Barton, R. H., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0001668 · Cited by 104
“altered mechanisms [33].”
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“Compared with the other omics methods, metabolomics has several advantages, including being significantly less expensive, not requiring a sequenced genome, and being more reflective of adverse effects than transcripts or proteins (Green et al., 2014; Clayton et al., 2006; Holmes et al., 2008; Sabatine et al., 2005; Sh…”
BackgroundCavill, R., Kamburov, A., Ellis, J. K., Athersuch, T. J., Blagrove, M. S. C., Herwig, R., Ebbels, T. M. D., & Keun, H. C. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001113 · Cited by 99
“Recently it has also been shown that pre-treatment metabolic profiles can be used to predict the metabolic fate or effect of drugs in rodents [48], healthy humans [49,50] and breast cancer patients [51].”
BackgroundMetabotyping of Caenorhabditis elegans reveals latent phenotypes
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“Among others, these include: Non-invasive biomarker investigations to discriminate between the different stages of progression of NAFLD using non-invasive biofluids (urine and plasma) [3,4]; investigation of mechanisms underlying hepatic disease progression such as acute-on-chronic liver failure using serum metabolic…”
BackgroundNMR metabolomics and drug discovery
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“We also observed a high degree of intrastrain variability in toxicity that has been reported by other investigators, particularly for the C57BL/6J mouse (Beyer et al., 2007) and the Sprague-Dawley rat (Clayton et al., 2006).”
ResultThe importance of biomarkers in neonatology
Mussap, M., Noto, A., Cibecchini, F., & Fanos, V. (2012) · Seminars in Fetal and Neonatal Medicine · doi:10.1016/j.siny.2012.10.006 · Cited by 97
Drugs, bugs, and personalized medicine: Pharmacometabonomics enters the ring
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“Pharmacometabonomics is a more recent approach that uses metabolic phenotypes to predict the metabolism or toxic effects of drugs (5).”
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Shintu, L., Baudoin, R., Navratil, V., Prot, J. M., Pontoizeau, C., Defernez, M., Blaise, B. J., Domange, C., Péry, A. R. R., Toulhoat, P., et al. (2012) · Analytical Chemistry · doi:10.1021/ac2011075 · Cited by 104
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“Metabolomics, generally defined as metabolic snap shots of living systems, is a holistic approach aimed at better understanding of primary and secondary metabolism of the biological systems (Clayton et al. 2006).”
Background“Omics” in pharmaceutical research: overview, applications, challenges, and future perspectives
Yan, S., Liu, R., Jin, H., Liu, X., Ye, J., Shan, L., & Zhang, W. (2015) · Chinese Journal of Natural Medicines · doi:10.1016/s1875-5364(15)60002-4 · Cited by 115
“In 2006, Clayton [98] applied (1)H NMR-based metabolomics to study an acetaminophen-induced liver toxicity model.”
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“One new approach, called ‘pharmaco-metabonomic phenotyping’, or simply ‘pharmacometabonomics’, has considerable potential to reveal the hidden significance of baseline metabolite profiles [3,4].”
BackgroundMetabolic phenotyping for monitoring surgical patients
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“We deliberately do not address the impact of individual genetic makeup [4,5] and environmental factors [6,7] on both mechanism of action and toxicity of drugs as the amount of available data is still very limited.”
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“Pharmacometabolomics is emerging as a discipline of metabolomics that studies the interplay between drug pharmacology and the patients’ (patho)physiology, by measuring endogenous metabolites that inform on variability in the drug PK or PD phenotype (Clayton et al. 2006; Kaddurah-Daouk and Weinshilboum 2015; Lindon et…”
BackgroundMetabolomics Applications in Precision Medicine: An Oncological Perspective
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BackgroundMultivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis
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“The use of pre-interventional phenotypes to predict the outcome of intervention based on mathematical modelling is termed ‘‘pharmacometabonomics” [10] and the approach has been widely used to predict drug metabolism [11] and outcomes of cancer therapy, toxicity [12] and safety.”
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Metabolomic approaches to phenotype characterization and applications to complex diseases
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Blood transcriptomics and metabolomics for personalized medicine
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“LC-MS/MS-based metabolomics has many important applications, including drug metabolism (19), biomarker discovery (20), personalization of therapy (21), and elucidation of drug action (22).”
BackgroundTranslational biomarkers of acetaminophen-induced acute liver injury
Beger, R. D., Bhattacharyya, S., Yang, X., Gill, P. S., Schnackenberg, L. K., Sun, J., & James, L. P. (2015) · Archives of Toxicology · doi:10.1007/s00204-015-1519-4 · Cited by 88
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Emerging New Strategies for Successful Metabolite Identification in Metabolomics
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BackgroundMetabolic profiling technologies for biomarker discovery in biomedicine and drug development.
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“dict the dominant metabolism of pharmaceutical compounds.(138)”
Nikolic, S. B., Sharman, J. E., Adams, M. J., & Edwards, L. M. (2014) · Journal of Hypertension · doi:10.1097/hjh.0000000000000168 · Cited by 79
“Since pharmacometabolomics offers the possibility to optimize treatment more effectively according to the metabolic profile of each individual and avoid adverse drug effects, this approach has major potential for developing personalized drug treatment [90].”
Corona, G., Rizzolio, F., Giordano, A., & Toffoli, G. (2011) · Journal of Cellular Physiology · doi:10.1002/jcp.24003 · Cited by 79
Drug metabolite profiling and elucidation of drug-induced hepatotoxicity
Tang, W. (2007) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1517/17425255.3.3.407 · Cited by 80
“Rat livers were examined for histologic damages [126].”
BackgroundThe role of metabolomics in neonatal and pediatric laboratory medicine
Mussap, M., Antonucci, R., Noto, A., & Fanos, V. (2013) · Clinica Chimica Acta · doi:10.1016/j.cca.2013.08.020 · Cited by 80
“By analyzing the metabolic modification due to drug treatments, metabolomics gives a number of information on the pharmacokinetic and pharmacodynamic response of an individual to the pharmacological therapy [113].”
BackgroundMonitoring the Health to Disease Continuum with Global Metabolic Profiling and Systems Biology
Schnackenberg, L. K., & Beger, R. D. (2006) · Pharmacogenomics · doi:10.2217/14622416.7.7.1077 · Cited by 65
In silicomodels for drug-induced liver injury – current status
Przybylak, K. R., & Cronin, M. (2012) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1517/17425255.2012.648613 · Cited by 82
“Apart from genomics, other omics-based technologies have produced many candidates for DILI biomarkers for future investigation, including those from metabolomics [33,54], transcriptomics [55] and proteomics [44].”
BackgroundPharmacometabonomics and personalized medicine
Everett, J. R., Loo, R. L., & Pullen, F. S. (2013) · Annals of Clinical Biochemistry International Journal of Laboratory Medicine · doi:10.1177/0004563213497929 · Cited by 75
“002).(11) From the loadings plot (Figure 6(d)), the most Figure 4.”
BackgroundMethodInfluentialSelf-citationWang, X.-J., Zhang, A., Sun, H., Han, Y., & Yan, G.-L. (2016) · doi:10.1016/j.trac.2015.11.010 · Cited by 75
Metabolomics in cancer: a bench-to-bedside intersection.
Claudino, W., Goncalves, P., Leo, A. D., Philip, P., & Sarkar, F. (2012) · Critical reviews in oncology/hematology · doi:10.1016/j.critrevonc.2012.02.009 · Cited by 75
Current Concepts in Pharmacometabolomics, Biomarker Discovery, and Precision Medicine
Beger, R. D., Schmidt, M. A., & Kaddurah‐Daouk, R. (2020) · Metabolites · doi:10.3390/metabo10040129 · Cited by 109
“The first pharmacometabonomics study found markers related to the metabolism of acetaminophen in humans and it was determined that the gut microbiota played a role in acetaminophen metabolism [10,64].”
BackgroundInfluentialAn HR-MAS MR Metabolomics Study on Breast Tissues Obtained with Core Needle Biopsy
Li, M.-L., Song, Y., Cho, N., Chang, J. M., Koo, H., Yi, A., Kim, H., Park, S., & Moon, W. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025563 · Cited by 74
“Magnetic resonance (MR) spectroscopic techniques has been a primary method employed in investigations of metabolite changes in biofluids such as urine, blood, and bile [1,2,3].”
MethodTang, W., & Lu, A. Y. H. (2009) · Drug Metabolism Reviews · doi:10.3109/03602530903401658 · Cited by 78
“In the experiment, animals were dosed with APAP, and their urine samples were analyzed by NMR before and after dosing (Clayton et al., 2006).”
MethodPhapale, P. B., Kim, S., Lee, H. W., Lim, M., Kale, D. D., Yl, K., Cho, J., Hwang, D., & Yoon, Y.-D. (2010) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2009.296 · Cited by 81
Miolo, G., Muraro, E., Caruso, D., Crivellari, D., Ash, A., Scalone, S., Lombardi, D., Rizzolio, F., Giordano, A., & Corona, G. (2016) · Oncotarget · doi:10.18632/oncotarget.9489 · Cited by 83
Metabolic shifts due to long-term caloric restriction revealed in nonhuman primates
Rezzi, S., Martin, F., Shanmuganayagam, D., Colman, R. J., Nicholson, J. K., & Weindruch, R. H. (2009) · Experimental Gerontology · doi:10.1016/j.exger.2009.02.008 · Cited by 80
“, 2002) and the pharmacometabonomic prediction of drug metabolism and toxicity from pre-dose metabolic models (Clayton et al., 2006).”
BackgroundMethodSelf-citationEnvironmental Influences in the Etiology of Colorectal Cancer: the Premise of Metabolomics
Rattray, N. J. W., Charkoftaki, G., Rattray, Z., Hansen, J. E., Vasiliou, V., & Johnson, C. H. (2017) · Current Pharmacology Reports · doi:10.1007/s40495-017-0088-z · Cited by 90
“Since the evolution of metabolomics in 1998 [110], the develo pmen t a nd g r ow t h o f t h e s u b - d i s c i p l i n e o f pharmacometabolomics [111] has blossomed to such an extent that a community-led White Paper has called for US Government inclusion of the area in to the highest level of”
BackgroundChikayama, E., Suto, M., Nishihara, T., Shinozaki, K., Hirayama, T., & Kikuchi, J. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003805 · Cited by 85
“Versatile sampling and robust H-NMR methods have improved disease diagnosis [9–12] and personalized healthcare [13–15], and have provided an important tool for the characterization of genetic variations [16].”
Metabolomics in drug research and development: The recent advances in technologies and applications
Pang, H., & Hu, Z. (2023) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2023.05.021 · Cited by 89
Metabolic Changes Reveal the Development of Schistosomiasis in Mice
Wu, J., Xu, W., Ming, Z., Dong, H., Tang, H., & Wang, Y. (2010) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0000807 · Cited by 75
“In supervised pattern recognition method, validation of model is crucial for interpretation of data and hence all models here have been rigorously evaluated with permutation tests (permutation numbers = 200) [39–40].”
MethodA Systematic Evaluation of Blood Serum and Plasma Pre-Analytics for Metabolomics Cohort Studies
Jobard, É., Trédan, O., Postoly, D., André, F., Martin, A., Elena‐Herrmann, B., & Boyault, S. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17122035 · Cited by 82
“It currently provides a wide range of new opportunities for the development of biomarkers of medical interest with current applications in toxicology [7], cancer [8–10], cardiovascular disease [11,12], prediction of treatment outcomes [13–15] or “pharmacometabonomics” [16,17], and more recently metabolic modelling of…”
Vehtari, A., Mäkinen, V., Soininen, P., Ingman, P., Mäkelä, S., Savolainen, M., Hannuksela, M., Kaski, K., & Ala-Korpela, M. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-s2-s8 · Cited by 70
“Recently, a call for applying 1H NMR metabonomics to facilitate disease risk assessment and clinical diagnostics has emerged [1,2, 4-8 ].”
BackgroundDiagnosing diabetic nephropathy by 1H NMR metabonomics of serum
Mäkinen, V., Soininen, P., Forsblom, C., Parkkonen, M., Ingman, P., Kaski, K., Groop, P., & Ala-Korpela, M. (2007) · Magnetic Resonance Materials in Physics, Biology and Medicine · doi:10.1007/s10334-006-0054-y · Cited by 70
“The promise of 1H NMR metabonomics of body fluids has recently been extensively highlighted in the biomedical arena [7,44].”
BackgroundPharmacogenomics: a systems approach
Wang, L. (2009) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.42 · Cited by 69
Are there meaningful biomarkers of treatment response for depression?
Breitenstein, B., Scheuer, S., & Holsboer, F. (2014) · Drug Discovery Today · doi:10.1016/j.drudis.2014.02.002 · Cited by 71
Hoy-Schulz, Y. E., Bik, E. M., Lawley, T. D., Holmes, S., Monack, D. M., Theriot, J. A., & Relman, D. A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0142825 · Cited by 77
“For example, since the composition of the microbiota and the presence of specific taxa are important for responses to drugs and susceptibility to specific pathogens [3,4,62], inter-individual differences in microbiota could result in differential responses to drugs or to pathogens.”
BackgroundLi, F., Lu, X.-M., Liu, H.-P., Liu, M., & Xiong, Z. (2007) · Biomedical chromotography · doi:10.1002/bmc.770 · Cited by 68
Human Breath Analysis May Support the Existence of Individual Metabolic Phenotypes
Sinues, P., Kohler, M., & Zenobi, R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059909 · Cited by 68
“For this reason, mapping of the metabolome and relating it to subpopulations or even individuals will be critical to fully achieve the concept of personalized healthcare [7].”
BackgroundYu, L.-Z., Aa, J., Xu, J., Sun, M., Qian, S., Cheng, L., Yang, S.-P., & Shi, R.-H. (2011) · Journal of Gastroenterology and Hepatology · doi:10.1111/j.1440-1746.2011.06724.x · Cited by 67
Prot, J. M., Bunescu, A., Elena‐Herrmann, B., Aninat, C., Snouber, L. C., Griscom, L., Razan, F., Bois, F. Y., Legallais, C., Brochot, C., et al. (2011) · Toxicology and Applied Pharmacology · doi:10.1016/j.taap.2011.12.017 · Cited by 71
“…(Nicholson et al., 1999; 2002), is a powerful tool for characterizing variations in the concentration of such compounds in biofluids or organs in response to drug treatments (Clayton et al., 2006), but also to pathophysiology (Dumas et al., 2006) or genetic polymorphisms (Dumas et al., 2007).”
The Application of Metabonomics to Predict Drug-Induced Liver Injury
O’Connell, T. M., & Watkins, P. B. (2010) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2010.151 · Cited by 68
Cosgrove, B. D., Alexopoulos, L. G., Hang, T.-C., Hendriks, B. S., Sorger, P. K., Griffith, L. G., & Lauffenburger, D. A. (2010) · Molecular BioSystems · doi:10.1039/b926287c · Cited by 58
PhRMA White Paper on ADME Pharmacogenomics
Williams, J. A., Andersson, T., Andersson, T. B., Blanchard, R. L., Behm, M. O., Cohen, N., Edeki, T. I., Franc, M. A., Hillgren, K. M., Johnson, K. J., et al. (2008) · The Journal of Clinical Pharmacology · doi:10.1177/0091270008319329 · Cited by 65
“Furthermore, there are a number of examples where genotypic differences (eg, different alleles) exist but do not affect the phenotype.(341) Such associations may not be sufficient for applications such as diagnostics but may still be useful for other purposes such as informing on the mechanism of drug metabolism and d…”
BackgroundWarren, J. S., Oka, S., Zablocki, D., & Sadoshima, J. (2017) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00103.2017 · Cited by 64
“Metabolomics has been used as part of personalized medicine to identify populations that will respond to a particular drug intervention (21).”
MethodKikuchi, J., Tsuboi, Y., Komatsu, K., Gomi, M., Chikayama, E., & Date, Y. (2015) · Analytical Chemistry · doi:10.1021/acs.analchem.5b02311 · Cited by 71
Zhao, L., Nicholson, J. K., Lü, A., Wang, Z., Tang, H., Holmes, E. C., Shen, J., Zhang, X., Li, J. V., & Lindon, J. C. (2012) · Journal of Proteome Research · doi:10.1021/pr3001628 · Cited by 66
Self-citationNicholson, J., Everett, J., & Lindon, J. (2012) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1517/17425255.2012.646987 · Cited by 64
“Although there is a partial overlap between the two groups of animals, a clear distinction is observed [4].”
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Metadata
- Authors
- Andrew Clayton, T., Lindon, J. C., Cloarec, O., Antti, H., Charuel, C., Hanton, G., Provost, J.-P., Le Net, J.-L., Baker, D., Walley, R. J., Everett, J. R., & Nicholson, J. K.
- Affiliations
- Imperial College London (GB)
- Umeå University (SE)
- Pfizer (France) (FR)
- Pfizer (United States) (US)
- Pfizer (United Kingdom) (GB)
- ORCID
- Venue
- Nature
- Published
- 2006-04-01
- Volume
- 440
- Issue
- 7087
- Pages
- 1073-1077
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W1968593126
- Cited by
- 824
- References
- 32
- Citations by year
- 2026: 10 · 2025: 21 · 2024: 17 · 2023: 31 · 2022: 27 · 2021: 29 · 2020: 29 · 2019: 32 · 2018: 39 · 2017: 39 · 2016: 50 · 2015: 62 · 2014: 57 · 2013: 47 · 2012: 62
- FWCI
- 53.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Greenwich Academic Literature Archive (University of Greenwich) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Pfizer
- Wellcome Trust
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Drug-Induced Hepatotoxicity and Protection
- Keywords
- drug response prediction, urinary metabolites, paracetamol, liver injury, interindividual variability, gut microbiota, chemometrics
- MeSH terms
- Acetaminophen, Animals, Environment, Individuality, Liver, Male, Models, Biological, Magnetic Resonance Spectroscopy, Pharmacogenetics, Phenotype, Rats, Sprague-Dawley, Rats
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