The kidney is one of the main targets of drug toxicity, but early detection of renal damage is often difficult. As part of the InnoMed PredTox project, a collaborative effort aimed at assessing the value of combining omics technologies with conventional toxicology methods for improved preclinical safety assessment, we evaluated the performance of a panel of novel kidney biomarkers in preclinical toxicity studies. Rats were treated with a reference nephrotoxin or one of several proprietary compounds that were dropped from drug development in part due to renal toxicity. Animals were dosed at two dose levels for 1, 3, and 14 days. Putative kidney markers, including kidney injury molecule-1 (Kim-1), lipocalin-2 (Lcn2), clusterin, and tissue inhibitor of metalloproteinases-1, were analyzed in kidney and urine using quantitative real-time PCR, ELISA, and immunohistochemistry. Changes in gene/protein expression generally correlated well with renal histopathological alterations and were frequently detected at earlier time points or at lower doses than the traditional clinical parameters blood urea nitrogen and serum creatinine. Urinary Kim-1 and clusterin reflected changes in gene/protein expression and histopathological alterations in the target organ in the absence of functional changes. This confirms clusterin and Kim-1 as early and sensitive, noninvasive markers of renal injury. Although Lcn2 did not appear to be specific for kidney toxicity, its rapid response to inflammation and tissue damage in general may suggest its utility in routine toxicity testing.

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There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPAR␣ activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis cou- The inability of current preclinical toxicology evaluation methods to predict early, and with good accuracy, that a drug candidate will have to be removed from development (or from the market) because of toxicicity/safety issues is a serious bottleneck in the drug development pipeline (1). Novel omics profiling technologies have the potential to provide more effective preclinical predictive models for toxicity (2). By performing detailed and comprehensive molecular profiling of animal or cell-based models that have been exposed to known toxic insults, it should be possible to catalog the spectrum of molecular changes that cause or accompany a particular mechanism of toxicity. It is reasonable to assume that molecular changes underlying, or induced by, toxicologic mechanisms will be manifested at earlier time points and at lower dose levels than are required for classical toxicology evaluation endpoints. Hence, the basic premise of preclinical predictive systems toxicology is to perform molecular profiling experiments for a range of compounds, potentially hundreds, displaying various toxicities and derivin...

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A serious bottleneck in the drug development pipeline is the inability of current pre-clinical toxicology evaluation methods to predict early on, and with good accuracy, that a drug candidate will have to be removed from development due to toxicology/safety issues. The InnoMed PredTox consortium attempted to address this issue by assessing the value of using molecular profiling techniques (proteomics, transcriptomics, and metabonomics), in combination with conventional toxicology measurements, on decision making earlier in pre-clinical safety evaluation. In this study, we report on the SELDI-TOF-MS proteomics component of the InnoMed PredTox project. In this large scale, multi-site, multi-compound study, tissue and plasma samples from 14-day in vivo rat experiments conducted for 16 hepato- and nephro-toxicants with known toxicology endpoints (including 14 proprietary compounds and 2 reference compounds) were analyzed by SELDI-TOF-MS. We have identified seven plasma proteins and four liver proteins which were shown to be modulated by treatment, and correlated with histopathological evaluations and can be considered potential biomarker candidates for the given toxicology endpoints. In addition, we report on the intra- and inter-site variations observed based on measurements from a reference sample, and steps that can be taken to minimize this variation.