ArticleBioMed research international2013
Prediction of clinically relevant safety signals of nephrotoxicity through plasma metabolite profiling.
Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Molecular signatures of angiogenesis inhibitors: a single-embryo untargeted metabolomics approach in zebrafish.Archives of toxicology · 2024Article
- Analytical and Omics-Based Advances in the Study of Drug-Induced Liver Injury.Toxicological sciences : an official journal of the Society of Toxicology · 2021Review
- Identification of Novel Biomarkers for Predicting Kidney Injury Due to Drugs Using "Omic" Strategies.Pharmacogenomics and personalized medicine · 2020Review
- Use cases, best practice and reporting standards for metabolomics in regulatory toxicology.Nature communications · 2019Review
- Zebrafish Larvae Are a Suitable Model to Investigate the Metabolic Phenotype of Drug-Induced Renal Tubular Injury.Frontiers in pharmacology · 2018Article
- Concurrent profiling of polar metabolites and lipids in human plasma using HILIC-FTMS.Scientific reports · 2016Article
- Metabolomics as a tool to evaluate the toxicity of formulations containing amphotericin B, an antileishmanial drug.Toxicology research · 2016Article
- Fast Filtration of Bacterial or Mammalian Suspension Cell Cultures for Optimal Metabolomics Results.PloS one · 2016Article
- Identification of a metabolic biomarker panel in rats for prediction of acute and idiosyncratic hepatotoxicity.Computational and structural biotechnology journal · 2014Article
Corrections and comments
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Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Addressing safety concerns such as drug-induced kidney injury (DIKI) early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril) was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC). The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound's well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity), not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.