title: Prediction of clinically relevant safety signals of nephrotoxicity through plasma metabolite profiling.
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.
authors.affiliation: PharmPoint Consulting, Poolesville, MD 20837, USA.
authors.forename: W B
authors.initials: WB
authors.lastname: Mattes
authors.forename: H G
authors.initials: HG
authors.lastname: Kamp
authors.forename: E
authors.initials: E
authors.lastname: Fabian
authors.forename: M
authors.initials: M
authors.lastname: Herold
authors.forename: G
authors.initials: G
authors.lastname: Krennrich
authors.forename: R
authors.initials: R
authors.lastname: Looser
authors.forename: W
authors.initials: W
authors.lastname: Mellert
authors.forename: A
authors.initials: A
authors.lastname: Prokoudine
authors.forename: V
authors.initials: V
authors.lastname: Strauss
authors.forename: B
authors.initials: B
authors.lastname: van Ravenzwaay
authors.forename: T
authors.initials: T
authors.lastname: Walk
authors.forename: H
authors.initials: H
authors.lastname: Naraoka
authors.forename: K
authors.initials: K
authors.lastname: Omura
authors.forename: I
authors.initials: I
authors.lastname: Schuppe-Koistinen
authors.forename: S
authors.initials: S
authors.lastname: Nadanaciva
authors.forename: E D
authors.initials: ED
authors.lastname: Bush
authors.forename: N
authors.initials: N
authors.lastname: Moeller
authors.forename: P
authors.initials: P
authors.lastname: Ruiz-Noppinger
authors.forename: S P
authors.initials: SP
authors.lastname: Piccoli
mesh_terms: D000818:Animals; D002216:Captopril / Q000009:adverse effects; D016572:Cyclosporine / Q000009:adverse effects; D004317:Doxorubicin / Q000009:adverse effects; D064420:Drug-Related Side Effects and Adverse Reactions / Q000097:blood* / Q000175:diagnosis* / Q000378:metabolism; D005260:Female; D006801:Humans; D007674:Kidney Diseases / Q000097:blood* / Q000139:chemically induced* / Q000378:metabolism; D017706:Lisinopril / Q000009:adverse effects; D008297:Male; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D010672:Phenytoin / Q000009:adverse effects; D051381:Rats; D017208:Rats, Wistar
chemical_list: D010672:Phenytoin; D004317:Doxorubicin; D016572:Cyclosporine; D002216:Captopril; D017706:Lisinopril