Risk Assessment for Hepatobiliary Toxicity Liabilities in Drug Development

Risk assessment of hepatobiliary toxicities represents one of the greatest challenges and, more often than not, one of the most rewarding activities in which toxicologic pathologists can partake, and often times lead. This is in part because each liver toxicity picture is a bit different, informed by a broad range and diversity of relevant data, and also in part because the heavily relied upon animal models are imperfect regarding predictivity of hepatic effects in humans. Following identification and characterization of a hepatotoxicity hazard, typically in nonclinical toxicology studies, a holistic and integrated assessment of liver-relevant endpoints is conducted that typically incorporates ADME (absorption, distribution, metabolism, and excretion) information (ideally, including extensive transporter data, exposure margins, and possibly concentration of parent/metabolite at region of injury), target expression/function, in silico prediction data, in vitro hepatocyte data, liver/circulating biomarkers, and importantly, species specificity of any of these data. Of course, a thorough understanding, developed in close partnership with clinical colleagues, of the anticipated liver disease status of intended patient populations is paramount to hepatic risk assessment. This is particularly important since the likelihood of translatable determinant hepatic events observed in nonclinical models to occur in humans has been reasonably well established.

Spatially resolved characterization of tissue metabolic compartments in fasted and high-fat diet livers

Cells adapt their metabolism to physiological stimuli, and metabolic heterogeneity exists between cell types, within tissues, and subcellular compartments. The liver plays an essential role in maintaining whole-body metabolic homeostasis and is structurally defined by metabolic zones. These zones are well-understood on the transcriptomic level, but have not been comprehensively characterized on the metabolomic level. Mass spectrometry imaging (MSI) can be used to map hundreds of metabolites directly from a tissue section, offering an important advance to investigate metabolic heterogeneity in tissues compared to extraction-based metabolomics methods that analyze tissue metabolite profiles in bulk. We established a workflow for the preparation of tissue specimens for matrix-assisted laser desorption/ionization (MALDI) MSI that can be implemented to achieve broad coverage of central carbon, nucleotide, and lipid metabolism pathways. Herein, we used this approach to visualize the effect of nutrient stress and excess on liver metabolism. Our data revealed a highly organized metabolic tissue compartmentalization in livers, which becomes disrupted under high fat diet. Fasting caused changes in the abundance of several metabolites, including increased levels of fatty acids and TCA intermediates while fatty livers had higher levels of purine and pentose phosphate-related metabolites, which generate reducing equivalents to counteract oxidative stress. This spatially conserved approach allowed the visualization of liver metabolic compartmentalization at 30 μm pixel resolution and can be applied more broadly to yield new insights into metabolic heterogeneity in vivo.

The Emerging Role of the Innate Immune Response in Idiosyncratic Drug Reactions

Idiosyncratic drug reactions (IDRs) range from relatively common, mild reactions to rarer, potentially life-threatening adverse effects that pose significant risks to both human health and successful drug discovery. Most frequently, IDRs target the liver, skin, and blood or bone marrow. Clinical data indicate that most IDRs are mediated by an adaptive immune response against drug-modified proteins, formed when chemically reactive species of a drug bind to self-proteins, making them appear foreign to the immune system. Although much emphasis has been placed on characterizing the clinical presentation of IDRs and noting implicated drugs, limited research has focused on the mechanisms preceding the manifestations of these severe responses. Therefore, we propose that to address the knowledge gap between drug administration and onset of a severe IDR, more research is required to understand IDR-initiating mechanisms; namely, the role of the innate immune response. In this review, we outline the immune processes involved from neoantigen formation to the result of the formation of the immunologic synapse and suggest that this framework be applied to IDR research. Using four drugs associated with severe IDRs as examples (amoxicillin, amodiaquine, clozapine, and nevirapine), we also summarize clinical and animal model data that are supportive of an early innate immune response. Finally, we discuss how understanding the early steps in innate immune activation in the development of an adaptive IDR will be fundamental in risk assessment during drug development. SIGNIFICANCE STATEMENT: Although there is some understanding that certain adaptive immune mechanisms are involved in the development of idiosyncratic drug reactions, the early phase of these immune responses remains largely uncharacterized. The presented framework refocuses the investigation of IDR pathogenesis from severe clinical manifestations to the initiating innate immune mechanisms that, in contrast, may be quite mild or clinically silent. A comprehensive understanding of these early influences on IDR onset is crucial for accurate risk prediction, IDR prevention, and therapeutic intervention.

Applications of mass spectrometry imaging in virus research

Mass spectrometry imaging (MSI) is a label-free molecular imaging technique allowing an untargeted detection of a broad range of biomolecules and xenobiotics. MSI enables imaging of the spatial distribution of proteins, peptides, lipids and metabolites from a wide range of samples. To date, this technique is commonly applied to tissue sections in cancer diagnostics and biomarker development, but also molecular histology in general. Advances in the methodology and bioinformatics improved the resolution of MS images below the single cell level and increased the flexibility of the workflow. However, MSI-based research in virology is just starting to gain momentum and its full potential has not been exploited yet. In this review, we discuss the main applications of MSI in virology. We review important aspects of matrix-assisted laser desorption/ionization (MALDI) MSI, the most widely used MSI technique in virology. In addition, we summarize relevant literature on MSI studies that aim to unravel virus-host interactions and virus pathogenesis, to elucidate antiviral drug kinetics and to improve current viral disease diagnostics. Collectively, these studies strongly improve our general understanding of virus-induced changes in the proteome, metabolome and metabolite distribution in host tissues of humans, animals and plants upon infection. Furthermore, latest MSI research provided important insights into the drug distribution and distribution kinetics, especially in antiretroviral research. Finally, MSI-based investigations of oncogenic viruses greatly increased our knowledge on tumor mass signatures and facilitated the identification of cancer biomarkers.

Combining MALDI mass spectrometry imaging and droplet-base surface sampling analysis for tissue distribution, metabolite profiling, and relative quantification of cyclic peptide melanotan II

Peptides have become a fast-growing segment of the pharmaceutical industry over the past few decades. It is essential to develop cutting edge analytical techniques to support the discovery and development of peptide therapeutics, especially to examine their absorption, distribution, metabolism and excretion (ADME) properties. Herein, we utilized two label-free mass spectrometry (MS) based techniques to investigate representative challenges in developing therapeutic peptides, such as tissue distribution, metabolic stability and clearance. A tool proof-of-concept cyclic peptide, melanotan II, was used in this study. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which is a well-developed label-free imaging technique, was used to map the detailed molecular distribution of melanotan II and its metabolites. Droplet-based liquid microjunction surface sampling liquid chromatography-high resolution mass spectrometry (LMJ-SSP-LC-HRMS) was used in combination with MALDI-MSI to rapidly profile molecular information and provide structural insights on drug and metabolites. Using both techniques in parallel allowed a more comprehensive and complementary data set than using either technique independently. We envision MALDI-MSI and droplet-based LMJ-SSP-LC-HRMS, which can be used in combination or as standalone techniques, to become valuable tools for assessing the in vivo fate of peptide therapeutics in support of drug discovery and development.

Periostin in chronic liver diseases: Current research and future perspectives

The liver is importantly metabolic and detoxifying organ in the body. When various pathogenic factors affect the liver, the normal physiological and biochemical functions are weakened, resulting in liver diseases. Liver fibrosis is a common pathological process of chronic liver disease. During hepatic fibrosis the changes in the components of the extracellular matrix (ECM) provide an environment that facilitates tissue remodeling. Among these ECM components, periostin, a glycoprotein that is predominantly secreted by osteoblasts and their precursors, playing an important role in bone formation, has attracted great attention. Periostin not only involves in bone metabolism, but also functions in modulating the cell fate determination, proliferation, inflammatory responses, even tumorigenesis of many other tissues and organs including liver. In different categories of liver disease patients, the serum and liver tissue levels of periostin were closely related to the decline of liver function, and the pathological stage. Numerous animal studies and experiments in vitro subsequently demonstrated that the abnormal expression of periostin resulted in metabolic disorders, liver inflammation, fibrosis and even tumorigenesis. Here we review the current progress on the role of periostin in pathologic pathways of liver system to explore whether periostin is a potential therapeutic target for the treatment of different liver diseases.

Deep Neural Network Models for Predicting Chemically Induced Liver Toxicity Endpoints From Transcriptomic Responses

Improving the accuracy of toxicity prediction models for liver injuries is a key element in evaluating the safety of drugs and chemicals. Mechanism-based information derived from expression (transcriptomic) data, in combination with machine-learning methods, promises to improve the accuracy and robustness of current toxicity prediction models. Deep neural networks (DNNs) have the advantage of automatically assembling the relevant features from a large number of input features. This makes them especially suitable for modeling transcriptomic data, which typically contain thousands of features. Here, we gaged gene- and pathway-level feature selection schemes using single- and multi-task DNN approaches in predicting chemically induced liver injuries (biliary hyperplasia, fibrosis, and necrosis) from whole-genome DNA microarray data. The single-task DNN models showed high predictive accuracy and endpoint specificity, with Matthews correlation coefficients for the three endpoints on 10-fold cross validation ranging from 0.56 to 0.89, with an average of 0.74 in the best feature sets. The DNN models outperformed Random Forest models in cross validation and showed better performance than Support Vector Machine models when tested in the external validation datasets. In the cross validation studies, the effect of the feature selection scheme was negligible among the studied feature sets. Further evaluation of the models on their ability to predict the injury phenotype per se for non-chemically induced injuries revealed the robust performance of the DNN models across these additional external testing datasets. Thus, the DNN models learned features specific to the injury phenotype contained in the gene expression data.

Role of xenobiotics in the induction and progression of fatty liver disease

Non-alcoholic fatty liver disease is a major cause of chronic liver pathology in humans. Fatty liver disease involves the accumulation of hepatocellular fat in hepatocytes that can progress to hepatitis. Steatohepatitis is categorized into alcoholic (ASH) or non-alcoholic (NASH) steatohepatitis based on the etiology of the insult. Both pathologies involve an initial steatosis followed by a progressive inflammation of the liver and eventual hepatic fibrosis (steatohepatitis) and cirrhosis. The involvement of pharmaceuticals and other chemicals in the initiation and progression of fatty liver disease has received increased study. This review will examine not only how xenobiotics initiate hepatic steatosis and steatohepatitis but also how the presence of fatty liver may modify the metabolism and pathologic effects of xenobiotics. The feeding of a high fat diet results in changes in the expression of nuclear receptors that are involved in adaptive and adverse liver effects following xenobiotic exposure. High fat diets also modulate cellular and molecular pathways involved in inflammation, metabolism, oxidative phosphorylation and cell growth. Understanding the role of hepatic steatosis and steatohepatitis on the sequelae of toxic and pathologic changes seen following xenobiotic exposure has importance in defining proper and meaningful human risk characterization of the drugs and other chemical agents.

Regulatory Forum Opinion Piece*: Imaging Applications in Toxicologic Pathology-Recommendations for Use in Regulated Nonclinical Toxicity Studies

Available imaging systems for use in preclinical toxicology studies increasingly show utility as important tools in the toxicologic pathologist's armamentarium, permit longitudinal evaluation of functional and morphological changes in tissues, and provide important information such as organ and lesion volume not obtained by conventional toxicology study parameters. Representative examples of practical imaging applications in toxicology research and preclinical studies are presented for ultrasound, positron emission tomography/single-photon emission computed tomography, optical, magnetic resonance imaging, and matrix-assisted laser desorption ionization-imaging mass spectrometry imaging. Some of the challenges for making imaging systems good laboratory practice-compliant for regulatory submission are presented. Use of imaging data on a case-by-case basis as part of safety evaluation in regulatory submissions is encouraged.

HBV, HCV, and HBV/HCV co-infection among HIV-positive patients in Hunan province, China: Regimen selection, hepatotoxicity, and antiretroviral therapy outcome

Co-infection with hepatitis B (HBV) and C (HCV) is common among people living with HIV (PLHIV). This study investigates the impacts of hepatitis co-infection on antiretroviral therapy (ART) outcomes and hepatotoxicity in PLHIV. The cohort study included 1984 PLHIV. Hepatotoxicity was defined by elevated alanine aminotransferase (ALT) levels. ART outcomes were measured by CD4 cell counts, viral load, and mortality rate in patients. Among 1984 PLHIV, 184 (9.3%) were co-infected with HBV and 198 (10.0%) with HCV and 54 (2.7%) were co-infected with HBV and HCV. Of these patients, 156 (7.9%) had ALT elevation ≥ grade 1 at baseline. During the course of ART, the mortality rate and its adjusted hazard ratio (AHR) in PLHIV who were co-infected with HCV (2.6/100 person-years [py], AHR = 2.3, 95%CI 1.1-4.7) was higher than for patients with mono-infected HIV, as it was for those with an elevated ALT (4.4/100 py, AHR = 3.8, [1.7-8.2]) at baseline compared to those with normal ALT. After 6-12 months of ART, the incidence of hepatotoxicity among all the patients was 3.7/100 py. The risk of hepatotoxicity was higher in HCV co-infected (18.6/100 py, adjusted odds ratio [AOR] = 12.4, [8.1-18.2]) than HIV mono-infected patients, and for all regimens (nevirapine: 30.0/100 py, 34.2, 7.3-47.9; zidovudine/stavudine: 24.7/100 py, 22.1, 7.1-25.5; efavirenz: 14.5/100 py, 9.4, 3.5-19.2; lopinavir/ritonavir: 40.1/100 py, 52.2, 9.5-88.2) except tenofovir (4.3/100 py, 4.9, 0.8-9.5). Patients with HBV/HCV co-infected had high hepatotoxicity (10.0/100 py, 6.3, 1.2-23.3) over the same period. Patients with HCV co-infection and HBV/HCV co-infection demonstrated higher hepatotoxicity rate compared with HIV mono-infected patients in China.

Application of Imaging Mass Spectrometry to Assess Ocular Drug Transit

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is becoming an important technology to determine the distribution of drugs and their metabolites in the tissue of preclinical species after dosing. Interest in IMS is growing in the ophthalmology field, but little work to this point has been done to investigate ocular drug transit using this technology. Information on where and how a drug is distributing through the eye is important in understanding efficacy and whether it is reaching the desired target tissue. For this study, ocular distribution of brimonidine was investigated in rabbits following topical administration. Brimonidine has been shown to lower intraocular pressure and is approved to treat glaucoma, the second leading cause of blindness in the world. We have developed IMS methods to assess transit of topically administered brimonidine from the anterior to the posterior segment of rabbit eyes. Using IMS, brimonidine was detected in the cornea, aqueous humor, iris, and posterior segments of the eye. The distribution of brimonidine suggests that the route of transit following topical administration is mainly through the uvea-scleral route. This study demonstrates that IMS can be applied to assess ocular transit and distribution of topically administered drugs.

Hepatocyte spheroids as a competent in vitro system for drug biotransformation studies: nevirapine as a bioactivation case study

The development of metabolically competent in vitro models is of utmost importance for predicting adverse drug reactions, thereby preventing attrition-related economical and clinical burdens. Using the antiretroviral drug nevirapine (NVP) as a model, this work aimed to validate rat hepatocyte 3D spheroid cultures as competent in vitro systems to assess drug metabolism and bioactivation. Hepatocyte spheroids were cultured for 12 days in a stirred tank system (3D cultures) and exposed to equimolar dosages of NVP and its two major Phase I metabolites, 12-OH-NVP and 2-OH-NVP. Phase I NVP metabolites were detected in the 3D cultures during the whole culture time in the same relative proportions reported in in vivo studies. Moreover, the modulation of SULT1A1 activity by NVP and 2-OH-NVP was observed for the first time, pointing their synergistic effect as a key factor in the formation of the toxic metabolite (12-sulfoxy-NVP). Covalent adducts formed by reactive NVP metabolites with N-acetyl-L-cysteine and bovine serum albumin were also detected by high-resolution mass spectrometry, providing new evidence on the relative role of the reactive NVP metabolites, 12-sulfoxy-NVP, and NVP quinone methide, in toxicity versus excretion pathways. In conclusion, these results demonstrate the validity of the 3D culture system to evaluate drug bioactivation, enabling the identification of potential biomarkers of bioactivation/toxicity, and providing new evidence to the mechanisms underlying NVP-induced toxic events. This model, integrated with the analytical strategies described herein, is of anticipated usefulness to the pharmaceutical industry, as an upstream methodology for flagging drug safety alerts in early stages of drug development.