Soy Protein Containing Diet Attenuates Murine Drug Exposure and Activity via Hepatic and Intestinal Cytochrome P450 Induction.

Pharmacokinetic variability in drug plasma exposure between different studies within the same species is not unexpected due to a variety of factors (such as differences in formulation, active pharmaceutical ingredient salt form and solid-state, genetic strain, sex, environmental, disease status, bioanalysis methods, circadian rhythms, etc.) although variability from within the same research group typically does not occur to a great degree because these variables are commonly controlled. Surprisingly, a pharmacology proof of concept study with a previously validated tool compound from the literature failed to show expected response in murine glucose-6-phosphate isomerase-induced arthritis model which was tied to compound plasma exposure unexpectedly 10-fold lower than exposure observed from early pharmacokinetic study confirming adequate exposure prior to proof of concept. A systematic series of studies were conducted to investigate causes for exposure difference between pharmacology and pharmacokinetic studies identifying the presence or absence of soy protein in animal chow as the causative variable. Cyp3a11 expression in intestine and liver was determined to increase in a time dependent manner in mice switched to diets containing soybean meal compared with mice on diets without soybean meal. The repeated pharmacology experiments using the soybean meal free diet achieved plasma exposures that were maintained above the EC50 and showed efficacy and proof of concept for the target. This effect was further confirmed with marker CYP3A4 substrates in follow on mouse studies. The role of soy protein containing diets on CYP expression necessitates the inclusion of controlling rodent diet as a variable for preventing possible exposure differences between studies. SIGNIFICANCE STATEMENT: The presence of soybean meal protein in murine diet increased clearance and decreased oral exposure for select cytochrome 3A4 substrates. Related effects were also observed on select liver enzyme expression.

An Overview of Machine Learning and Big Data for Drug Toxicity Evaluation.

Drug toxicity evaluation is an essential process of drug development as it is reportedly responsible for the attrition of approximately 30% of drug candidates. The rapid increase in the number and types of large toxicology data sets together with the advances in computational methods may be used to improve many steps in drug safety evaluation. The development of in silico models to screen and understand mechanisms of drug toxicity may be particularly beneficial in the early stages of drug development where early toxicity assessment can most reduce expenses and labor time. To facilitate this, machine learning methods have been employed to evaluate drug toxicity but are often limited by small and less diverse data sets. Recent advances in machine learning methods together with the rapid increase in big toxicity data such as molecular descriptors, toxicogenomics, and high-throughput bioactivity data may help alleviate some of the current challenges. In this article, the most common machine learning methods used in toxicity assessment are reviewed together with examples of toxicity studies that have used machine learning methodology. Furthermore, a comprehensive overview of the different types of toxicity tools and data sets available to build in silico toxicity prediction models has been provided to give an overview of the current big toxicity data landscape and highlight opportunities and challenges related to them.

Transcriptomic evaluation of canine suspension-shipped and pre-plated hepatocytes: comparison to liver.

INTRODUCTION: In vitro assays using rat and human hepatocytes are used for hepatotoxicity studies; however, in vitro methods are less established for canine hepatocytes. In particular, little is known about the effects of plating and culture on canine hepatocytes. The goal of this study was to conduct a descriptive analysis of an in vitro canine hepatocyte system to evaluate its utility and limitations. The study objectives were to determine if canine hepatocytes shipped in suspension or pre-plated were transcriptomically different from one another and their liver of origin, and to understand temporal transcriptomic changes. MATERIALS AND METHODS: Frozen canine liver samples were delivered on dry ice; hepatocytes from these livers were delivered in a cell/media suspension (S) or pre-plated (P). Hepatocytes were harvested at arrival and after up to 120 hr of culture in naïve media, or after 48 hr treatment with prototypical enzyme inducing xenobiotics (phenobarbital or rifampin). RESULTS: A global transcriptomic comparison between liver and hepatocyte preparations indicated that the transcriptome was affected post-plating; transporters and genes involved in xenobiotic metabolism were generally down-regulated. Basal mRNA levels of CYP3A12 and CYP2B11 decreased temporally; after 120 hr CYP3A12 levels decreased by 1000-fold. CYP3A12 and CYP2B11 induction after phenobarbital or rifampin treatment was robust in both cell types but stronger in S cells. CONCLUSIONS: These results indicate that S and P hepatocytes cultured under the current conditions are appropriate for specific in vitro tests. Further characterization of endpoints should be conducted for a thorough understanding of the model's limitations.

Off-target pharmacological activity at various kinases: Potential functional and pathological side effects.

In drug discovery, during the lead optimization and candidate characterization stages, novel small molecules are frequently evaluated in a battery of in vitro pharmacology assays to identify potential unintended, off-target interactions with various receptors, transporters, ion channels, and enzymes, including kinases. Furthermore, these screening panels may also provide utility at later stages of development to provide a mechanistic understanding of unexpected safety findings. Here, we present a compendium of the most likely functional and pathological outcomes associated with interaction(s) to a panel of 95 kinases based on an extensive curation of the scientific literature. This panel of kinases was designed by AbbVie based on safety-related data extracted from the literature, as well as from over 20 years of institutional knowledge generated from discovery efforts. For each kinase, the scientific literature was reviewed using online databases and the most often reported functional and pathological effects were summarized. This work should serve as a practical guide for small molecule drug discovery scientists and clinical investigators to predict and/or interpret adverse effects related to pharmacological interactions with these kinases.

A systems approach reveals species differences in hepatic stress response capacity.

To minimize the occurrence of unexpected toxicities in early phase preclinical studies of new drugs, it is vital to understand fundamental similarities and differences between preclinical species and humans. Species differences in sensitivity to acetaminophen (APAP) liver injury have been related to differences in the fraction of the drug that is bioactivated to the reactive metabolite N-acetyl-p-benzoquinoneimine (NAPQI). We have used physiologically based pharmacokinetic modeling to identify oral doses of APAP (300 and 1000 mg/kg in mice and rats, respectively) yielding similar hepatic burdens of NAPQI to enable the comparison of temporal liver tissue responses under conditions of equivalent chemical insult. Despite pharmacokinetic and biochemical verification of the equivalent NAPQI insult, serum biomarker and tissue histopathology analyses revealed that mice still exhibited a greater degree of liver injury than rats. Transcriptomic and proteomic analyses highlighted the stronger activation of stress response pathways (including the Nrf2 oxidative stress response and autophagy) in the livers of rats, indicative of a more robust transcriptional adaptation to the equivalent insult. Components of these pathways were also found to be expressed at a higher basal level in the livers of rats compared with both mice and humans. Our findings exemplify a systems approach to understanding differential species sensitivity to hepatotoxicity. Multiomics analysis indicated that rats possess a greater basal and adaptive capacity for hepatic stress responses than mice and humans, with important implications for species selection and human translation in the safety testing of new drug candidates associated with reactive metabolite formation.

Preclinical species gene expression database: Development and meta-analysis.

The evaluation of toxicity in preclinical species is important for identifying potential safety liabilities of experimental medicines. Toxicology studies provide translational insight into potential adverse clinical findings, but data interpretation may be limited due to our understanding of cross-species biological differences. With the recent technological advances in sequencing and analyzing omics data, gene expression data can be used to predict cross species biological differences and improve experimental design and toxicology data interpretation. However, interpreting the translational significance of toxicogenomics analyses can pose a challenge due to the lack of comprehensive preclinical gene expression datasets. In this work, we performed RNA-sequencing across four preclinical species/strains widely used for safety assessment (CD1 mouse, Sprague Dawley rat, Beagle dog, and Cynomolgus monkey) in ∼50 relevant tissues/organs to establish a comprehensive preclinical gene expression body atlas for both males and females. In addition, we performed a meta-analysis across the large dataset to highlight species and tissue differences that may be relevant for drug safety analyses. Further, we made these databases available to the scientific community. This multi-species, tissue-, and sex-specific transcriptomic database should serve as a valuable resource to enable informed safety decision-making not only during drug development, but also in a variety of disciplines that use these preclinical species.

Role of cytochrome P450c17α in dibromoacetic acid-induced testicular toxicity in rats.

Dibromoacetic acid (DBAA), a by-product formed during disinfection of drinking water, alters spermatogenesis in rats through defective spermiation. The mechanism underlying this toxicity is not fully understood. In this study, gene expression data generated with microarrays from testes were used to generate a mechanistic understanding of DBAA-induced testicular toxicity. Testes were collected from male Sprague-Dawley rats dosed orally for 1 and 4 days with DBAA at 250 mg/kg/day. At both time points, DBAA administration induced delayed spermiation in Stage X tubules and regulated the expression of a small number of genes, including a mild but consistent downregulation of cytochrome P450c17α (CYP17) mRNA, an enzyme expressed by Leydig cells and essential for the production of testicular androgens. Downregulation of CYP17 was confirmed at the protein level and its biological significance was substantiated by demonstrating reduced testicular testosterone levels in DBAA-dosed rats. Furthermore, testosterone production by human chorionic gonadotrophin (hCG)-stimulated rat primary Leydig cells was reduced following treatment with 100 µM DBAA. Collectively, these results indicate that DBAA can directly target rat Leydig cells and downregulate testicular CYP17 expression with a resulting decreased testicular testosterone production. This disruption of testicular steroidogenesis is likely to contribute to the mechanism of failed spermiation observed in rats following exposure to DBAA.

Global transcriptomic profiling using small volumes of whole blood: a cost-effective method for translational genomic biomarker identification in small animals.

Blood is an ideal tissue for the identification of novel genomic biomarkers for toxicity or efficacy. However, using blood for transcriptomic profiling presents significant technical challenges due to the transcriptomic changes induced by ex vivo handling and the interference of highly abundant globin mRNA. Most whole blood RNA stabilization and isolation methods also require significant volumes of blood, limiting their effective use in small animal species, such as rodents. To overcome these challenges, a QIAzol-based RNA stabilization and isolation method (QSI) was developed to isolate sufficient amounts of high quality total RNA from 25 to 500 µL of rat whole blood. The method was compared to the standard PAXgene Blood RNA System using blood collected from rats exposed to saline or lipopolysaccharide (LPS). The QSI method yielded an average of 54 ng total RNA per µL of rat whole blood with an average RNA Integrity Number (RIN) of 9, a performance comparable with the standard PAXgene method. Total RNA samples were further processed using the NuGEN Ovation Whole Blood Solution system and cDNA was hybridized to Affymetrix Rat Genome 230 2.0 Arrays. The microarray QC parameters using RNA isolated with the QSI method were within the acceptable range for microarray analysis. The transcriptomic profiles were highly correlated with those using RNA isolated with the PAXgene method and were consistent with expected LPS-induced inflammatory responses. The present study demonstrated that the QSI method coupled with NuGEN Ovation Whole Blood Solution system is cost-effective and particularly suitable for transcriptomic profiling of minimal volumes of whole blood, typical of those obtained with small animal species.

Comparison of TNFα to lipopolysaccharide as an inflammagen to characterize the idiosyncratic hepatotoxicity potential of drugs: Trovafloxacin as an example.

Idiosyncratic drug reactions (IDRs) are poorly understood, unpredictable, and not detected in preclinical studies. Although the cause of these reactions is likely multi-factorial, one hypothesis is that an underlying inflammatory state lowers the tolerance to a xenobiotic. Previously used in an inflammation IDR model, bacterial lipopolysaccharide (LPS) is heterogeneous in nature, making development of standardized testing protocols difficult. Here, the use of rat tumor necrosis factor-α (TNFα) to replace LPS as an inflammatory stimulus was investigated. Sprague-Dawley rats were treated with separate preparations of LPS or TNFα, and hepatic transcriptomic effects were compared. TNFα showed enhanced consistency at the transcriptomic level compared to LPS. TNFα and LPS regulated similar biochemical pathways, although LPS was associated with more robust inflammatory signaling than TNFα. Rats were then codosed with TNFα and trovafloxacin (TVX), an IDR-associated drug, and evaluated by liver histopathology, clinical chemistry, and gene expression analysis. TNFα/TVX induced unique gene expression changes that clustered separately from TNFα/levofloxacin, a drug not associated with IDRs. TNFα/TVX cotreatment led to autoinduction of TNFα resulting in potentiation of underlying gene expression stress signals. Comparison of TNFα/TVX and LPS/TVX gene expression profiles revealed similarities in the regulation of biochemical pathways. In conclusion, TNFα could be used in lieu of LPS as an inflammatory stimulus in this model of IDRs.

Managing the challenge of drug-induced liver injury: a roadmap for the development and deployment of preclinical predictive models.

Drug-induced liver injury (DILI) is a patient-specific, temporal, multifactorial pathophysiological process that cannot yet be recapitulated in a single in vitro model. Current preclinical testing regimes for the detection of human DILI thus remain inadequate. A systematic and concerted research effort is required to address the deficiencies in current models and to present a defined approach towards the development of new or adapted model systems for DILI prediction. This Perspective defines the current status of available models and the mechanistic understanding of DILI, and proposes our vision of a roadmap for the development of predictive preclinical models of human DILI.

Screening Strategies and Methods for Better Off-Target Liability Prediction and Identification of Small-Molecule Pharmaceuticals.

Pharmaceutical discovery and development is a long and expensive process that, unfortunately, still results in a low success rate, with drug safety continuing to be a major impedance. Improved safety screening strategies and methods are needed to more effectively fill this critical gap. Recent advances in informatics are now making it possible to manage bigger data sets and integrate multiple sources of screening data in a manner that can potentially improve the selection of higher-quality drug candidates. Integrated screening paradigms have become the norm in Pharma, both in discovery screening and in the identification of off-target toxicity mechanisms during later-stage development. Furthermore, advances in computational methods are making in silico screens more relevant and suggest that they may represent a feasible option for augmenting the current screening paradigm. This paper outlines several fundamental methods of the current drug screening processes across Pharma and emerging techniques/technologies that promise to improve molecule selection. In addition, the authors discuss integrated screening strategies and provide examples of advanced screening paradigms.

Novel Computational Approach to Predict Off-Target Interactions for Small Molecules.

Most small molecule drugs interact with unintended, often unknown, biological targets and these off-target interactions may lead to both preclinical and clinical toxic events. Undesired off-target interactions are often not detected using current drug discovery assays, such as experimental polypharmacological screens. Thus, improvement in the early identification of off-target interactions represents an opportunity to reduce safety-related attrition rates during preclinical and clinical development. In order to better identify potential off-target interactions that could be linked to predictable safety issues, a novel computational approach to predict safety-relevant interactions currently not covered was designed and evaluated. These analyses, termed Off-Target Safety Assessment (OTSA), cover more than 7,000 targets (~35% of the proteome) and > 2,46,704 preclinical and clinical alerts (as of January 20, 2019). The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known in vitro activities derived from patents, journals, and publicly available databases. This computational process was used to predict both the primary and secondary pharmacological activities for a selection of 857 diverse small molecule drugs for which extensive secondary pharmacology data are readily available (456 discontinued and 401 FDA approved). The OTSA process predicted a total of 7,990 interactions for these 857 molecules. Of these, 3,923 and 4,067 possible high-scoring interactions were predicted for the discontinued and approved drugs, respectively, translating to an average of 9.3 interactions per drug. The OTSA process correctly identified the known pharmacological targets for >70% of these drugs, but also predicted a significant number of off-targets that may provide additional insight into observed in vivo effects. About 51.5% (2,025) and 22% (900) of these predicted high-scoring interactions have not previously been reported for the discontinued and approved drugs, respectively, and these may have a potential for repurposing efforts. Moreover, for both drug categories, higher promiscuity was observed for compounds with a MW range of 300 to 500, TPSA of ~200, and clogP ≥7. This computation also revealed significantly lower promiscuity (i.e., number of confirmed off-targets) for compounds with MW > 700 and MW<200 for both categories. In addition, 15 internal small molecules with known off-target interactions were evaluated. For these compounds, the OTSA framework not only captured about 56.8% of in vitro confirmed off-target interactions, but also identified the right pharmacological targets for 14 compounds as one of the top scoring targets. In conclusion, the OTSA process demonstrates good predictive performance characteristics and represents an additional tool with utility during the lead optimization stage of the drug discovery process. Additionally, the computed physiochemical properties such as clogP (i.e., lipophilicity), molecular weight, pKa and logS (i.e., solubility) were found to be statistically different between the approved and discontinued drugs, but the internal compounds were close to the approved drugs space in most part.

Potential mechanisms of target-independent uptake and toxicity of antibody-drug conjugates.

Antibody-drug conjugates (ADCs) are a promising therapeutic modality for oncology indications. The concept of an ADC platform is to increase the therapeutic index (TI) of chemotherapeutics through more selective delivery of cytotoxic agents to tumor cells while limiting exposure to healthy normal cells. Despite the use of antibodies targeting antigens abundantly and/or exclusively expressed on cancer cells (i.e., target cells), dose limiting toxicities (DLTs) in normal cells/tissues are frequently reported even at suboptimal therapeutic doses. Although advancement of ADC technology has helped to optimize all three key components (i.e., mAb, linker, and payload), DLTs remain a key challenge for ADC development. Mechanisms of ADC toxicity in normal cells/tissues are not clearly understood, but the majority of DLTs are considered to be target-independent. In addition to linker-drug instability contributing to the premature release of cytotoxic drug (payload) in circulation, uptake/trafficking of intact ADCs by both receptor-dependent (FcγRs, FcRn and C-type lectin receptors), and-independent (non-specific endocytosis) mechanisms may contribute to off-target toxicity in normal cells. In this article, we review potential mechanisms of target-independent ADC uptake and toxicity in normal cells, as well as discuss components of ADCs which may influence these mechanisms. This information will provide a deeper understanding of the underlying mechanisms of ADC off-target toxicity and prove helpful toward improving the overall TI of the next generation of ADCs.

Gene expression profiles in livers from diclofenac-treated rats reveal intestinal bacteria-dependent and -independent pathways associated with liver injury.

Diclofenac (DCLF) is a nonsteroidal anti-inflammatory drug that is associated with idiosyncratic adverse drug reactions in humans. Previous studies revealed a crucial role for intestine-derived bacteria and/or lipopolysaccharide (LPS) in DCLF-induced hepatotoxicity. We further explored this mechanism by conducting gene expression analysis of livers from rats treated with a hepatotoxic dose of DCLF (100 mg/kg) with or without oral antibiotic pretreatment. Genes for which expression was altered by DCLF were divided into two groups: genes with expression altered by antibiotic treatment and those unaffected by antibiotics. The former group of genes represented the ones for which DCLF-induced alterations in expression depended on intestinal bacteria. The expression of the latter group of genes was probably changed by direct effect of DCLF rather than by intestinal bacteria. Functional analysis of genes in the former group revealed LPS-related signaling, further suggesting a role for bacterial endotoxin in the liver injury. Functional analysis of genes in the latter group revealed changes in signaling pathways related to inflammation, hypoxia, oxidative stress, the aryl hydrocarbon receptor, and peroxisome proliferator-activated receptor alpha. Neutrophil depletion failed to protect from DCLF-induced hepatotoxicity, suggesting that intestinal bacteria contribute to liver injury in a neutrophil-independent manner. Hypoxia occurred in the livers of rats treated with DCLF, and hypoxia in vitro rendered hepatocytes sensitive to DCLF-induced cytotoxicity. These results support the hypothesis that intestinal bacteria are required for DCLF-induced hepatotoxicity and suggest that hypoxia plays an important role in the pathogenesis.

Trovafloxacin-induced gene expression changes in liver-derived in vitro systems: comparison of primary human hepatocytes to HepG2 cells.

Primary human hepatocytes (PHH) are a main instrument in drug metabolism research and in the prediction of drug-induced phase I/II enzyme induction in humans. The HepG2 liver-derived cell line is commonly used as a surrogate for human hepatocytes, but its use in absorption, distribution, metabolism, and excretion and toxicity studies can be limited because of lowered basal levels of metabolizing enzymes. Despite the widespread use of HepG2 cells, a comparison of their transcriptomes with those of PHH has not been well characterized. In this study, microarray analysis was conducted to ascertain the differences and similarities in mRNA expression between HepG2 cells and human hepatocytes before and after exposure to a panel of fluoroquinolone compounds. Comparison of the naive HepG2 cell and PHH transcriptomes revealed a substantial number of basal gene expression differences. When HepG2 cells were dosed with a series of fluoroquinolones, trovafloxacin (TVX), which has been associated with human idiosyncratic hepatotoxicity, induced substantially more gene expression changes than the other quinolones, similar to previous observations with PHH. Although TVX-treatment resulted in many gene expression differences between HepG2 cells and PHH, there were also a number of TVX-induced commonalities, including genes involved in RNA processing and mitochondrial function. Taken together, these results provide insight for interpretation of results from drug metabolism and toxicity studies conducted with HepG2 cells in lieu of PHH and could provide further insight into the mechanistic evaluation of TVX-induced hepatotoxicity.

Comparison of RNA-Seq and Microarray Gene Expression Platforms for the Toxicogenomic Evaluation of Liver From Short-Term Rat Toxicity Studies.

Gene expression profiling is a useful tool to predict and interrogate mechanisms of toxicity. RNA-Seq technology has emerged as an attractive alternative to traditional microarray platforms for conducting transcriptional profiling. The objective of this work was to compare both transcriptomic platforms to determine whether RNA-Seq offered significant advantages over microarrays for toxicogenomic studies. RNA samples from the livers of rats treated for 5 days with five tool hepatotoxicants (α-naphthylisothiocyanate/ANIT, carbon tetrachloride/CCl4, methylenedianiline/MDA, acetaminophen/APAP, and diclofenac/DCLF) were analyzed with both gene expression platforms (RNA-Seq and microarray). Data were compared to determine any potential added scientific (i.e., better biological or toxicological insight) value offered by RNA-Seq compared to microarrays. RNA-Seq identified more differentially expressed protein-coding genes and provided a wider quantitative range of expression level changes when compared to microarrays. Both platforms identified a larger number of differentially expressed genes (DEGs) in livers of rats treated with ANIT, MDA, and CCl4 compared to APAP and DCLF, in agreement with the severity of histopathological findings. Approximately 78% of DEGs identified with microarrays overlapped with RNA-Seq data, with a Spearman's correlation of 0.7 to 0.83. Consistent with the mechanisms of toxicity of ANIT, APAP, MDA and CCl4, both platforms identified dysregulation of liver relevant pathways such as Nrf2, cholesterol biosynthesis, eiF2, hepatic cholestasis, glutathione and LPS/IL-1 mediated RXR inhibition. RNA-Seq data showed additional DEGs that not only significantly enriched these pathways, but also suggested modulation of additional liver relevant pathways. In addition, RNA-Seq enabled the identification of non-coding DEGs that offer a potential for improved mechanistic clarity. Overall, these results indicate that RNA-Seq is an acceptable alternative platform to microarrays for rat toxicogenomic studies with several advantages. Because of its wider dynamic range as well as its ability to identify a larger number of DEGs, RNA-Seq may generate more insight into mechanisms of toxicity. However, more extensive reference data will be necessary to fully leverage these additional RNA-Seq data, especially for non-coding sequences.

Test systems in drug discovery for hazard identification and risk assessment of human drug-induced liver injury.

INTRODUCTION: The liver is an important target for drug-induced toxicities. Early detection of hepatotoxic drugs requires use of well-characterized test systems, yet current knowledge, gaps and limitations of tests employed remains an important issue for drug development. Areas Covered: The current state of the science, understanding and application of test systems in use for the detection of drug-induced cytotoxicity, mitochondrial toxicity, cholestasis and inflammation is summarized. The test systems highlighted herein cover mostly in vitro and some in vivo models and endpoint measurements used in the assessment of small molecule toxic liabilities. Opportunities for research efforts in areas necessitating the development of specific tests and improved mechanistic understanding are highlighted. Expert Opinion: Use of in vitro test systems for safety optimization will remain a core activity in drug discovery. Substantial inroads have been made with a number of assays established for human Drug-induced Liver Injury. There nevertheless remain significant gaps with a need for improved in vitro tools and novel tests to address specific mechanisms of human Drug-Induced Liver Injury. Progress in these areas will necessitate not only models fit for application, but also mechanistic understanding of how chemical insult on the liver occurs in order to identify translational and quantifiable readouts for decision-making.

Investigations toward enhanced understanding of hepatic idiosyncratic drug reactions.

Idiosyncratic drug reactions (IDRs) of a hepatic origin are a major health concern and a notoriously difficult challenge for the pharmaceutical industry. These types of adverse events are rare, with a typical occurrence of 1 in 100 to 1 in 100,000 patients. Typical adverse outcomes are most likely statistically impossible to predict in traditional preclinical safety studies or clinical trials. Unfortunately, these reactions can pose a significant risk to the public health, resulting in devastating consequences such as irreversible liver injury, liver transplantation and fatality. This review provides many examples of experimental efforts that are underway for a better understanding of molecular events that may be responsible for IDRs. A list of existing hypotheses for IDRs is also provided, each with current literature examples or supporting evidence. The possibilities for developing suitable animal models for the prediction and characterisation of IDRs are elaborated, especially for a drug-inflammation interaction rat model of hepatic IDR. The need for predictive biomarkers of IDR is addressed, with the exploration of some possible candidates. Finally, the use of primary human hepatocyte culture systems is explored as an in vitro system, with application for providing an increased mechanistic knowledge of IDR. Several examples of informative studies on the nature of IDRs that employ toxicogenomic and proteomic technologies are summarised.

Biomarker evaluation of skeletal muscle toxicity following clofibrate administration in rats.

The use of sensitive biomarkers to monitor skeletal muscle toxicity in preclinical toxicity studies is important for the risk assessment in humans during the development of a novel compound. Skeletal muscle toxicity in Sprague Dawley Rats was induced with clofibrate at different dose levels for 7 days to compare standard clinical pathology assays with novel skeletal muscle and cardiac muscle biomarkers, gene expression and histopathological changes. The standard clinical pathology assays aspartate aminotransferase (AST), alanine aminotransferase (ALT), and creatine kinase (CK) enzyme activity were compared to novel biomarkers fatty acid binding protein 3 (Fabp3), myosin light chain 3 (Myl3), muscular isoform of CK immunoreactivity (three isoforms CKBB, CKMM, CKMB), parvalbumin (Prv), skeletal troponin I (sTnI), cardiac troponin T (cTnT), cardiac troponin I (cTnI), CKMM, and myoglobin (Myo). The biomarker elevations were correlated to histopathological findings detected in several muscles and gene expression changes. Clofibrate predominantly induced skeletal muscle toxicity of type I fibers of low magnitude. Useful biomarkers for skeletal muscle toxicity were AST, Fabp3, Myl3, (CKMB) and sTnI. Measurements of CK enzyme activity by a standard clinical assay were not useful for monitoring clofibrate-induced skeletal muscle toxicity in the rat at the doses used in this study.

Anti-repulsive Guidance Molecule C (RGMc) Antibodies Increases Serum Iron in Rats and Cynomolgus Monkeys by Hepcidin Downregulation.

High levels of hepcidin, the main regulator of systemic iron metabolism, lead to various diseases. Targeting hepcidin and lowering its concentration is a possible form of intervention in order to treat these diseases. High turnover rate of hepcidin is a major drawback of therapies directly targeting this peptide. We developed two monoclonal antibodies ABT-207 and h5F9-AM8 which inhibit hemojuvelin/repulsive guidance molecule C (RGMc) and downregulate hepcidin. We conducted single-application and dose response studies to understand the antibodies' mechanism and subchronic toxicology studies to exclude safety-related concerns. Investigation was carried out at different biological levels through qPCR, Affymetrix, liquid chromatography coupled with mass spectrometry (LC-MS/MS), histopathology, serum iron, unsaturated iron binding capacity (UIBC), and drug concentration measurements. After a single application of these antibodies, hepcidin expression in liver and its serum protein levels were reduced. Serum iron increased for several weeks. The RGMc antibodies show a pronounced dose response relationship in rats with h5F9-AM8 having an IC50 (UIBC) of approximately 80-fold higher than ABT-207. When hepcidin levels were downregulated, iron deposition in the liver was visible histologically 1 week post application. These antibody-mediated iron depositions were not associated with any adverse toxicologically relevant effect at the doses and time points evaluated. Iron depositions seen after 14 weekly treatments with ABT-207 were reversible in rats and in cynomolgus monkeys. Due to their long-lasting effects and excellent safety profile, both RGMc-blocking antibodies ABT-207 and h5F9-AM8 are favorable clinical candidates for diseases characterized by high serum hepcidin levels like anemia of chronic disease.