Novel Mechanisms of Valproate Hepatotoxicity: Impaired Mrp2 Trafficking and Hepatocyte Depolarization

Advances and Challenges in Modeling Cannabidiol Pharmacokinetics and Hepatotoxicity

Cannabidiol (CBD) is a pharmacologically active metabolite of cannabis that is US Food and Drug Administration approved to treat seizures associated with Lennox-Gastaut syndrome, Dravet syndrome, and tuberous sclerosis complex in children aged 1 year and older. During clinical trials, CBD caused dose-dependent hepatocellular toxicity at therapeutic doses. The risk for toxicity was increased in patients taking valproate, another hepatotoxic antiepileptic drug, through an unknown mechanism. With the growing popularity of CBD in the consumer market, an improved understanding of the safety risks associated with CBD is needed to ensure public health. This review details current efforts to describe CBD pharmacokinetics and mechanisms of hepatotoxicity using both pharmacokinetic models and in vitro models of the liver. In addition, current evidence and knowledge gaps related to intracellular mechanisms of CBD-induced hepatotoxicity are described. The authors propose future directions that combine systems-based models with markers of CBD-induced hepatotoxicity to understand how CBD pharmacokinetics may influence the adverse effect profile and risk of liver injury for those taking CBD. SIGNIFICANCE STATEMENT: This review describes current pharmacokinetic modeling approaches to capture the metabolic clearance and safety profile of cannabidiol (CBD). CBD is an increasingly popular natural product and US Food and Drug Administration-approved antiepileptic drug known to cause clinically significant enzyme-mediated drug interactions and hepatotoxicity at therapeutic doses. CBD metabolism, pharmacokinetics, and putative mechanisms of CBD-induced liver injury are summarized from available preclinical data to inform future modeling efforts for understanding CBD toxicity.

Assessing Liver Effects of Cannabidiol and Valproate Alone and in Combination Using Quantitative Systems Toxicology

In clinical trials of cannabidiol (CBD) for the treatment of seizures in patients with Dravet syndrome, Lennox-Gastaut syndrome, and tuberous sclerosis complex, elevations in serum alanine aminotransferase (ALT) > 3× the upper limit of normal were observed in some patents, but the incidence was much greater in patients who were receiving treatment with valproate (VPA) before starting CBD. To explore potential mechanisms underlying this interaction, we used DILIsym, a quantitative systems toxicology model, to predict ALT elevations in a simulated human population treated with CBD alone, VPA alone, and when CBD dosing was starting during treatment with VPA. We gathered in vitro data assessing the potential for CBD, the two major CBD metabolites, and VPA to cause hepatotoxicity via inhibition of bile acid transporters, mitochondrial dysfunction, and production of reactive oxygen species (ROS). Physiologically-based pharmacokinetic models for CBD and VPA were used to predict liver exposure. DILIsym simulations predicted dose-dependent ALT elevations from CBD treatment and this was predominantly driven by ROS production from the parent molecule. DILIsym also predicted VPA treatment to cause ALT elevations which were transient when mitochondrial biogenesis was incorporated into the model. Contrary to the clinical experience, simulation of 2 weeks treatment with VPA prior to introduction of CBD treatment did not predict an increase of the incidence of ALT elevations relative to CBD treatment alone. We conclude that the marked increased incidence of CBD-associated ALT elevations in patients already receiving VPA is unlikely to involve the three major mechanisms of direct hepatotoxicity.

An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph-based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly "Question-of-the-Month (QotM) Challenge" series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

Molecular and Clinical Links between Drug-Induced Cholestasis and Familial Intrahepatic Cholestasis

Idiosyncratic Drug-Induced Liver Injury (iDILI) represents an actual health challenge, accounting for more than 40% of hepatitis cases in adults over 50 years and more than 50% of acute fulminant hepatic failure cases. In addition, approximately 30% of iDILI are cholestatic (drug-induced cholestasis (DIC)). The liver's metabolism and clearance of lipophilic drugs depend on their emission into the bile. Therefore, many medications cause cholestasis through their interaction with hepatic transporters. The main canalicular efflux transport proteins include: 1. the bile salt export pump (BSEP) protein (ABCB11); 2. the multidrug resistance protein-2 (MRP2, ABCC2) regulating the bile salts' independent flow by excretion of glutathione; 3. the multidrug resistance-1 protein (MDR1, ABCB1) that transports organic cations; 4. the multidrug resistance-3 protein (MDR3, ABCB4). Two of the most known proteins involved in bile acids' (BAs) metabolism and transport are BSEP and MDR3. BSEP inhibition by drugs leads to reduced BAs' secretion and their retention within hepatocytes, exiting in cholestasis, while mutations in the ABCB4 gene expose the biliary epithelium to the injurious detergent actions of BAs, thus increasing susceptibility to DIC. Herein, we review the leading molecular pathways behind the DIC, the links with the other clinical forms of familial intrahepatic cholestasis, and, finally, the main cholestasis-inducing drugs.

Potential risk of liver injury in epileptic patients during COVID-19 pandemic

Most of the antiseizure medications (ASMs) are metabolized in liver and many of them particularly first-generation ASMs have the potential to increase liver enzymes or induce liver injury. Hence, treatment of new onset seizures or epilepsy by ASMs during the course of coronavirus disease 2019 (COVID-19), which could potentially be complicated by hepatic dysfunction, is a challenging clinical issue. Intravenous form of levetiracetam which has no significant hepatic metabolism or drug-drug interaction is often a favorable option to control seizures in acute phase of COVID-19. Administration of enzyme inducer ASMs and valproate with the well-known hepatotoxicity and common drug interactions is not generally recommended. In patients with epilepsy who are under control with potentially hepatotoxic ASMs, close observation and cautious dose reduction or drug switch should be considered if any evidence of hepatic impairment exists. However, risks of possible breakthrough seizures should be weighed against benefits of lowering the hazard of liver injury. In patients with epilepsy who receive polytherapy with ASMs, transient dose modification with the tendency to increase the dose of ASMs with more favorable safety profile and less drug interaction and decrease the dose of drugs with main hepatic metabolism, high protein binding, potential to cause liver injury and known drug-drug reaction should be considered. Finally, decision making should be individualized based on patients' conditions and course of illness.

Pentylenetetrazole kindling-induced epilepsy rat models: Insight on the severity state, a comparative study

This study aimed to carry out a comparative study of the main models of chronic epilepsy induced by pentylenetetrazole (PTZ)-kindling method and to assess the efficacy of sodium valproate, one of the main antiepileptics, on the best epilepsy-inducing kindling model. Two sets of 24 animals were divided into 4 groups of 6 animals and treated as follow: Set 1 included: group 1, control; group 2, the classic kindling PTZ group (UKEOD); group 3, PTZ kindling every other day group with challenge (CKEOD); group 4, PTZ kindling every day group, with challenge (CKED); Set 2 included: group 1, control; group 2, CKEOD group; group 3 and 4, receiving either valproate 200 mg/kg or valproate 300 mg/kg + CKEOD procedure. Results show that CKEOD group significantly reduced the number of injections necessary to reach the fully-kindled state, increased the severity of seizures and improved the stability of seizures. In addition, the CKEOD group significantly increased the level of malondialdehyde and GABA transaminase, reduced the level of reduced glutathione, catalase and GABA. Furthermore, it had no impact on plasma levels of alanine aminotransferase (ALAT) and aspartate aminotransferase (ASAT). Valproate 300 mg/kg significantly protected animals against kindling induced by CKEOD. The kindling model with a challenge dose administered on day 1 (CKEOD) thus allows to induce more severe, more stable chronic epilepsy and in a shorter period of time, and could thus contribute to a better understanding of epilepsy, as well as its uses in drug discovery.

Collagen Sandwich Culture of Primary Hepatocytes for Image-Based Investigations

Collagen sandwich culture of hepatocytes retains many in vivo-like properties and is used for many investigations in liver cell biology, and hepatic pharmacology and toxicology. This chapter describes the method of establishing collagen sandwich culture of hepatocytes in a glass bottom dish for image-based studies.

Switching of cell fate through the regulation of cell growth during drug-induced intrahepatic cholestasis

Understanding the fundamental mechanisms that govern the fate of cells during drug-induced intrahepatic cholestasis provides strategies for the establishment of evaluation methods for drug screening. In the present study, the aggregates of a differentiated human hepatic cell line, HepaRG, were incubated in medium with Y27632 or bosentan to clarify the changes in the behavior of bile canaliculi (BC) with the growth of cells during drug-induced intrahepatic cholestasis. With elapsed exposure time, the aggregates in the culture with bosentan caused the dilation of BC, and the hepatocytes ultimately exhibited apoptotic death after the disruption of BC. Y27632 caused the disruption of BC in the aggregates after dilation. However, there was no change in the number of cells within the aggregates in the culture with Y27632, in spite of its cytotoxicity. After 144 h from the start of Y27632 exposure, the aggregates showed the rearrangement of BC. To inhibit cell division, the aggregates exposed to Y27632, which exhibited disruption of BC, were treated with mitomycin C for 2 h and continuously exposed to Y27632. The inhibition of cell division could not induce the rearrangement of BC within these aggregates, which was similar to the phenomenon observed in the aggregates exposed to bosentan. These findings indicate that growth is an important factor that influences the switching of cell fate toward survival or death in drug-induced intrahepatic cholestasis process. Thus, the autoregulation of growth is a major contributor to the rearrangement of BC within aggregates.

Quantifying drug-induced structural toxicity in hepatocytes and cardiomyocytes derived from hiPSCs using a deep learning method

Cardiac and hepatic toxicity result from induced disruption of the functioning of cardiomyocytes and hepatocytes, respectively, which is tightly related to the organization of their subcellular structures. Cellular structure can be analyzed from microscopy imaging data. However, subtle or complex structural changes that are not easily perceived may be missed by conventional image-analysis techniques. Here we report the evaluation of PhenoTox, an image-based deep-learning method of quantifying drug-induced structural changes using human hepatocytes and cardiomyocytes derived from human induced pluripotent stem cells. We assessed the ability of the deep learning method to detect variations in the organization of cellular structures from images of fixed or live cells. We also evaluated the power and sensitivity of the method for detecting toxic effects of drugs by conducting a set of experiments using known toxicants and other methods of screening for cytotoxic effects. Moreover, we used PhenoTox to characterize the effects of tamoxifen and doxorubicin-which cause liver toxicity-on hepatocytes. PhenoTox revealed differences related to loss of cytochrome P450 3A4 activity, for which it showed greater sensitivity than a caspase 3/7 assay. Finally, PhenoTox detected structural toxicity in cardiomyocytes, which was correlated with contractility defects induced by doxorubicin, erlotinib, and sorafenib. Taken together, the results demonstrated that PhenoTox can capture the subtle morphological changes that are early signs of toxicity in both hepatocytes and cardiomyocytes.