Immune drug-induced liver disease and drugs

Microphysiological Models for Mechanistic-Based Prediction of Idiosyncratic DILI

Drug-induced liver injury (DILI) is a major contributor to high attrition rates among candidate and market drugs and a key regulatory, industry, and global health concern. While acute and dose-dependent DILI, namely, intrinsic DILI, is predictable and often reproducible in preclinical models, the nature of idiosyncratic DILI (iDILI) limits its mechanistic understanding due to the complex disease pathogenesis, and recapitulation using in vitro and in vivo models is extremely challenging. However, hepatic inflammation is a key feature of iDILI primarily orchestrated by the innate and adaptive immune system. This review summarizes the in vitro co-culture models that exploit the role of the immune system to investigate iDILI. Particularly, this review focuses on advancements in human-based 3D multicellular models attempting to supplement in vivo models that often lack predictability and display interspecies variations. Exploiting the immune-mediated mechanisms of iDILI, the inclusion of non-parenchymal cells in these hepatoxicity models, namely, Kupffer cells, stellate cells, dendritic cells, and liver sinusoidal endothelial cells, introduces heterotypic cell-cell interactions and mimics the hepatic microenvironment. Additionally, drugs recalled from the market in the US between 1996-2010 that were studies in these various models highlight the necessity for further harmonization and comparison of model characteristics. Challenges regarding disease-related endpoints, mimicking 3D architecture with different cell-cell contact, cell source, and the underlying multi-cellular and multi-stage mechanisms are described. It is our belief that progressing our understanding of the underlying pathogenesis of iDILI will provide mechanistic clues and a method for drug safety screening to better predict liver injury in clinical trials and post-marketing.

New bismuth oxyiodide/chitosan nanocomposite for ultrasonic waves expedited adsorptive removal of amoxicillin from aqueous medium: kinetic, isotherm and thermodynamic investigations

Amoxicillin (AMX) is a widely used antibiotic, which induces harmful effects to nature via bioaccumulation and persistence in the environment if discharged untreated into water bodies. In the current study, a novel bionanocomposite, bismuth oxyiodide-chitosan (BiOI-Ch), was synthesized by a facile precipitation method and its amoxicillin (AMX) adsorption capacity in the presence of ultrasonic waves has been explored. Multiple batch experiments were performed to achieve the optimum operational parameters for maximum adsorption of AMX and the obtained results were as follows: pH 3, 80 mg g^-1 AMX concentration, 1.7 g L^-1 adsorbent dose, temperature 298 K and ultrasonication time 20 min. Composite removed approximately 90% AMX from the solution under optimized conditions, while the maximal adsorption capacity was determined to be 81.01 mg g^-1. BiOI-Ch exhibited superior adsorption capacity as compared to pure BiOI (33.78 mg g^-1). To understand the dynamics of reaction, several kinetic and isotherm models were also examined. The adsorption process obeyed pseudo-second-order kinetic model (R² = 0.98) and was well fitted to Freundlich isotherm (R² = 0.99). The addition of biowaste chitosan to non-toxic bismuth-based nanoparticles coupled with ultrasonication led to enhanced functional groups as well as surface area of the nanocomposite resulting in superior adsorption capacity, fast adsorption kinetics and improved mass transfer for the removal of AMX molecules. Thus, this study demonstrates the synergistic effect of ultrasonication in improved performance of novel BiOI-Ch for potential application in the elimination of persistent and detrimental pollutants from industrial effluent after necessary optimization for large-scale operation.

Recent Advances in Models of Immune-Mediated Drug-Induced Liver Injury

Hepatic inflammation is a key feature of a variety of liver diseases including drug-induced liver injury (DILI), orchestrated by the innate immune response (Kupffer cells, monocytes, neutrophils, dendritic cells) and the adaptive immune system (T cells and natural killer T cells). In contrast to acute DILI, prediction of immune-mediated DILI (im-DILI) has been more challenging due to complex disease pathogenesis, lack of reliable models and limited knowledge of underlying mechanisms. This review summarizes in vivo and in vitro systems that have been used to model im-DILI. In particular, the review focuses on state-of-the-art in vitro human-based multicellular models which have been developed to supplement the use of in vivo models due to interspecies variation and increasing ethical concerns regarding animal use. Advantages of the co-cultures in maintaining hepatocyte functions and importantly, introducing heterotypic cell-cell interactions to mimic inflammatory hepatic microenvironment are discussed. Challenges regarding cell source and incorporation of different cells with physical cell-cell contact are outlined and potential solutions are proposed. It is likely that better understanding of the interplay of immune cells in liver models will allow for the development of more accurate systems to better predict hepatotoxicity and stratification of drugs that can cause immune-mediated effects.

Role of immune dysfunction in drug induced liver injury

Drug-induced liver injury (DILI) is one of the leading causes of liver failure and withdrawal of drugs from the market. A poor understanding of the precipitating event aetiology and mechanisms of disease progression has rendered the prediction and subsequent treatment intractable. Recent literature suggests that some drugs can alter the liver’s repair systems resulting in injury. The pathophysiology of DILI is complex, and immune dysfunction plays an important role in determining the course and severity of the disease. Immune dysfunction is influenced by the host response to drug toxicity. A deeper understanding of these processes may be beneficial in the management of DILI and aid in drug development. This review provides a structured framework presenting DILI in three progressive stages that summarize the interplay between drugs and the host defence networks.

Nilotinib-Induced Immune-Mediated Liver Injury: Corticosteroid as a Possible Therapeutic Option

Introduction: Nilotinib is a BCR-ABL tyrosine kinase inhibitor approved for chronic myeloid leukemia. We present a case of severe immune-mediated liver injury by nilotinib treatment.

Case report: A 59-year-old woman was referred to the liver clinic because of elevated liver enzyme levels. One year prior, she was diagnosed as having chronic myeloid leukemia and treated with nilotinib therapy. The level of aspartate aminotransferase and alanine aminotransferase were 578 IU/L and 499 IU/L, respectively. Percutaneous needle liver biopsy showed extensive centrilobular infiltration of immune cells and destruction of the lobular architecture with minimal inflammation in the portal triad. Immunohistochemical staining showed that many CD8⁺ T cells and CD56⁺ cells infiltrated the site of inflammation. Multicolor fluorescence-activated cell-sorting analysis revealed that a considerable number of intrahepatic CD8+ T cells showed an activated phenotype compared with the healthy control. She was diagnosed with nilotinib-induced, immune-mediated liver injury. Prednisolone treatment (30 mg daily) was started and caused rapid normalization of liver enzyme levels.

Conclusion: Nilotinib can cause immune-mediated liver injury. The use of corticosteroid can be treatment option in immune-mediated liver injury.

Advancing Predictive Hepatotoxicity at the Intersection of Experimental, in Silico, and Artificial Intelligence Technologies

Adverse drug reactions, particularly those that result in drug-induced liver injury (DILI), are a major cause of drug failure in clinical trials and drug withdrawals. Hepatotoxicity-mediated drug attrition occurs despite substantial investments of time and money in developing cellular assays, animal models, and computational models to predict its occurrence in humans. Underperformance in predicting hepatotoxicity associated with drugs and drug candidates has been attributed to existing gaps in our understanding of the mechanisms involved in driving hepatic injury after these compounds perfuse and are metabolized by the liver. Herein we assess in vitro, in vivo (animal), and in silico strategies used to develop predictive DILI models. We address the effectiveness of several two- and three-dimensional in vitro cellular methods that are frequently employed in hepatotoxicity screens and how they can be used to predict DILI in humans. We also explore how humanized animal models can recapitulate human drug metabolic profiles and associated liver injury. Finally, we highlight the maturation of computational methods for predicting hepatotoxicity, the untapped potential of artificial intelligence for improving in silico DILI screens, and how knowledge acquired from these predictions can shape the refinement of experimental methods.