Search

We present a hypothetical case study to examine the use of a next-generation framework developed by the Genetic Toxicology Technical Committee of the Health and Environmental Sciences Institute for assessing the potential risk of genetic damage from a pharmaceutical perspective. We used etoposide, a genotoxic carcinogen, as a representative pharmaceutical for the purposes of this case study. Using the framework as guidance, we formulated a hypothetical scenario for the use of etoposide to illustrate the application of the framework to pharmaceuticals. We collected available data on etoposide considered relevant for assessment of genetic toxicity risk. From the data collected, we conducted a quantitative analysis to estimate margins of exposure (MOEs) to characterize the risk of genetic damage that could be used for decision-making regarding the predefined hypothetical use. We found the framework useful for guiding the selection of appropriate tests and selecting relevant endpoints that reflected the potential for genetic damage in patients. The risk characterization, presented as MOEs, allows decision makers to discern how much benefit is critical to balance any adverse effect(s) that may be induced by the pharmaceutical. Interestingly, pharmaceutical development already incorporates several aspects of the framework per regulations and health authority expectations. Moreover, we observed that quality dose response data can be obtained with carefully planned but routinely conducted genetic toxicity testing. This case study demonstrates the utility of the next-generation framework to quantitatively model human risk based on genetic damage, as applicable to pharmaceuticals.

As legacy toxicogenomics databases have become available, improved data mining approaches are now key to extracting and visualizing subtle relationships between toxicants and gene expression. In the present study, a novel “aggregating bundles of clusters” (ABC) procedure was applied to separate cholestatic from non-cholestatic drugs and model toxicants in the Johnson & Johnson (Janssen) rat liver toxicogenomics database [3]. Drug-induced cholestasis is an important issue, particularly when a new compound enters the market with this liability, with standard preclinical models often mispredicting this toxicity. Three well-characterized cholestasis-responsive genes (Cyp7a1, Mrp3 and Bsep) were chosen from a previous in-house Janssen gene expression signature; these three genes show differing, non-redundant responses across the 90+ paradigm compounds in our database. Using the ABC procedure, extraneous contributions were minimized in comparisons of compound gene responses. All genes were assigned weights proportional to their correlations with Cyp7a1, Mrp3 and Bsep, and a resampling technique was used to derive a stable measure of compound similarity. The compounds that were known to be associated with rat cholestasis generally had small values of this measure relative to each other but also had large values of this measure relative to non-cholestatic compounds. Visualization of the data with the ABC-derived signature showed a very tight, essentially identically behaving cluster of robust human cholestatic drugs and experimental cholestatic toxicants (ethinyl estradiol, LPS, ANIT and methylene dianiline, disulfiram, naltrexone, methapyrilene, phenacetin, alpha-methyl dopa, flutamide, the NSAIDs–—indomethacin, flurbiprofen, diclofenac, flufenamic acid, sulindac, and nimesulide, butylated hydroxytoluene, piperonyl butoxide, and bromobenzene), some slightly less active compounds (3′-acetamidofluorene, amsacrine, hydralazine, tannic acid), some drugs that behaved very differently, and were distinct from both non-cholestatic and cholestatic drugs (ketoconazole, dipyridamole, cyproheptadine and aniline), and many postulated human cholestatic drugs that in rat showed no evidence of cholestasis (chlorpromazine, erythromycin, niacin, captopril, dapsone, rifampicin, glibenclamide, simvastatin, furosemide, tamoxifen, and sulfamethoxazole). Most of these latter drugs were noted previously by other groups as showing cholestasis only in humans. The results of this work suggest that the ABC procedure and similar statistical approaches can be instrumental in combining data to compare toxicants across toxicogenomics databases, extract similarities among responses and reduce unexplained data varation. Keywords: Cluster analysis, Cholestasis, Gene signature, Microarray, Prediction, Toxicogenomics

Colistin and polymyxin B are effective treatment options for Gram-negative resistant bacteria but are used as last-line therapy due to their dose-limiting nephrotoxicity. A critical factor in developing safer polymyxin analogues is understanding accumulation of the drugs and their metabolites, which is currently limited due to the lack of effective techniques for analysis of these challenging molecules. Mass spectrometry imaging (MSI) allows direct detection of targets (drugs, metabolites, and endogenous compounds) from tissue sections. The presented study exemplifies the utility of MSI by measuring the distribution of polymyxin B1, colistin, and polymyxin B nonapeptide (PMBN) within dosed rat kidney tissue sections. The label-free MSI analysis revealed that the nephrotoxic compounds (polymyxin B1 and colistin) preferentially accumulated in the renal cortical region. The less nephrotoxic analogue, polymyxin B nonapeptide, was more uniformly distributed throughout the kidney. In addition, metabolites of the dosed compounds were detected by MSI. Kidney homogenates were analyzed using LC/MS/MS to determine total drug exposure and for metabolite identification. To our knowledge, this is the first time such techniques have been utilized to measure the distribution of polymyxin drugs and their metabolites. By simultaneously detecting the distribution of drug and drug metabolites, MSI offers a powerful alternative to tissue homogenization analysis and label or antibody-based imaging.

Despite six decades of clinical experience with the polymyxin class of antibiotics, their dose-limiting nephrotoxicity remains difficult to predict due to a paucity of sensitive biomarkers. Here, we evaluate the performance of standard of care and next-generation biomarkers of renal injury in the detection and monitoring of polymyxin-induced acute kidney injury in male Han Wistar rats using colistin (polymyxin E) and a polymyxin B (PMB) derivative with reduced nephrotoxicity, PMB nonapeptide (PMBN). This study provides the first histopathological and biomarker analysis of PMBN, an important test of the hypothesis that fatty acid modifications and charge reductions in polymyxins can reduce their nephrotoxicity. The results indicate that alterations in a panel of urinary kidney injury biomarkers can be used to monitor histopathological injury, with Kim-1 and α-GST emerging as the most sensitive biomarkers outperforming clinical standards of care, serum or plasma creatinine and blood urea nitrogen. To enable the prediction of polymyxin-induced nephrotoxicity, an in vitro cytotoxicity assay was employed using human proximal tubule epithelial cells (HK-2). Cytotoxicity data in these HK-2 cells correlated with the renal toxicity detected via safety biomarker data and histopathological evaluation, suggesting that in vitro and in vivo methods can be incorporated within a screening cascade to prioritize polymyxin class analogs with more favorable renal toxicity profiles.

A new class of benzoxazole and benzothiazole amide derivatives exhibiting potent CYP3A4 inhibiting properties was identified. Extensive lead optimization was aimed at improving the CYP3A4 inhibitory properties as well as overall ADME profile of these amide derivatives. This led to the identification of thiazol-5-ylmethyl (2S,3R)-4-(2-(ethyl(methyl)amino)-N-isobutylbenzo[d]oxazole-6-carboxamido)-3-hydroxy-1-phenylbutan-2-ylcarbamate (C1) as a lead candidate for this class. This compound together with structurally similar analogues demonstrated excellent ‘boosting’ properties when tested in dogs. These findings warrant further evaluation of their properties in an effort to identify valuable alternatives to Ritonavir as pharmacokinetic enhancers.

The detection of drug-induced hepatotoxicity remains an important safety issue in drug development. A liver-specific microRNA species, microRNA-122 (miR-122), has recently shown potential for predicting liver injury in addition to the standard hepatic injury biomarkers. The objective of this study was to measure miR-122 together with several other liver markers in distinct settings of acute liver toxicity in rats to determine the value of miR-122 as a biomarker for liver injury in this species. Rats were exposed to 3 well-established liver toxicants (acetaminophen, allyl alcohol, and α-naphthyl isothiocyanate), a liver-enzyme inducer (phenobarbital), or a cardiotoxicant (doxorubicin). There was a clear increase in plasma miR-122 following administration of acetaminophen, allyl alcohol, and α-naphthyl isothiocyanate. The response of miR-122 paralleled that of other markers and was consistent with liver injury as indicated by histopathological evaluation. Furthermore, the changes in miR-122 were detected earlier than standard liver injury markers and exhibited a wide dynamic range. In contrast, miR-122 responses to phenobarbital and doxorubicin were low. Based on these findings, miR-122 shows significant promise and may provide added value for assessing liver toxicity in drug development.