topiramate and Chemical-and-Drug-Induced-Liver-Injury

Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Drug Labeling; Humans; Pharmaceutical Preparations; Risk

Topics: Anticonvulsants; Blood Coagulation Disorders; Cerebral Palsy; Chemical and Drug Induced Liver Injury; Child; Combined Modality Therapy; Drug Monitoring; Epilepsy; Fructose; Humans; Hyperammonemia; Intellectual Disability; Liver; Liver Failure, Acute; Male; Topiramate; Treatment Outcome

Data on drug-induced liver injury (DILI) caused by newer antiseizure medications (ASMs) in the elderly are scarce and mainly come from literature case reports. We analyzed Individual Case Safety Reports (ICSRs) of DILI in elderly patients treated with newer ASMs reported to VigiBase.. Empirica™ Signal software was used to retrieve ICSRs reported to VigiBase up to 31 December 2021 and to calculate Empirical Bayesian Geometric Mean and corresponding 90% confidence intervals (EB05, EB95) for each drug-event pair. EB05 > 2,. There were 1399 ICSRs reporting 1947 events of hepatotoxicity. 56.97% of the reports were reported in females, 67.05% were serious, and 3.36% resulted in death. For one or more events of hepatotoxicity, signals were detected for lamotrigine, levetiracetam, oxcarbazepine, topiramate, and zonisamide. Age- and gender-biased reporting frequency was identified for topiramate-induced hyperammonemia, with disproportionally higher reporting frequency in ≥75-year-old male patients.. The results of our study indicate differences among newer ASMs in their potential to cause DILI in the elderly. Further studies are needed to confirm the associations identified in this study.

Topics: Aged; Anticonvulsants; Bayes Theorem; Chemical and Drug Induced Liver Injury; Drug-Related Side Effects and Adverse Reactions; Female; Humans; Levetiracetam; Male; Topiramate

The bile salt export pump (BSEP) is expressed at the canalicular domain of hepatocytes, where it serves as the primary route of elimination for monovalent bile acids (BAs) into the bile canaliculi. The most compelling evidence linking dysfunction in BA transport with liver injury in humans is found with carriers of mutations that render BSEP nonfunctional. Based on mounting evidence, there appears to be a strong association between drug-induced BSEP interference and liver injury in humans; however, causality has not been established. For this reason, drug-induced BSEP interference is best considered a susceptibility factor for liver injury as other host- or drug-related properties may contribute to the development of hepatotoxicity. To better understand the association between BSEP interference and liver injury in humans, over 600 marketed or withdrawn drugs were evaluated in BSEP expressing membrane vesicles. The example of a compound that failed during phase 1 human trials is also described, AMG 009. AMG 009 showed evidence of liver injury in humans that was not predicted by preclinical safety studies, and BSEP inhibition was implicated. For 109 of the drugs with some effect on in vitro BSEP function, clinical use, associations with hepatotoxicity, pharmacokinetic data, and other information were annotated. A steady state concentration (C(ss)) for each of these annotated drugs was estimated, and a ratio between this value and measured IC₅₀ potency values were calculated in an attempt to relate exposure to in vitro potencies. When factoring for exposure, 95% of the annotated compounds with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 were associated with some form of liver injury. We then investigated the relationship between clinical evidence of liver injury and effects to multidrug resistance-associated proteins (MRPs) believed to play a role in BA homeostasis. The effect of 600+ drugs on MRP2, MRP3, and MRP4 function was also evaluated in membrane vesicle assays. Drugs with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 and a C(ss)/MRP IC₅₀ ratio ≥ 0.1 had almost a 100% correlation with some evidence of liver injury in humans. These data suggest that integration of exposure data, and knowledge of an effect to not only BSEP but also one or more of the MRPs, is a useful tool for informing the potential for liver injury due to altered BA transport.

Topics: Animals; ATP Binding Cassette Transporter, Subfamily B; ATP Binding Cassette Transporter, Subfamily B, Member 11; ATP-Binding Cassette Transporters; Biological Transport; Chemical and Drug Induced Liver Injury; Cluster Analysis; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Male; Multidrug Resistance-Associated Proteins; Pharmacokinetics; Rats; Rats, Sprague-Dawley; Recombinant Proteins; Risk Assessment; Risk Factors; Toxicity Tests

The human bile salt export pump (BSEP) is a membrane protein expressed on the canalicular plasma membrane domain of hepatocytes, which mediates active transport of unconjugated and conjugated bile salts from liver cells into bile. BSEP activity therefore plays an important role in bile flow. In humans, genetically inherited defects in BSEP expression or activity cause cholestatic liver injury, and many drugs that cause cholestatic drug-induced liver injury (DILI) in humans have been shown to inhibit BSEP activity in vitro and in vivo. These findings suggest that inhibition of BSEP activity by drugs could be one of the mechanisms that initiate human DILI. To gain insight into the chemical features responsible for BSEP inhibition, we have used a recently described in vitro membrane vesicle BSEP inhibition assay to quantify transporter inhibition for a set of 624 compounds. The relationship between BSEP inhibition and molecular physicochemical properties was investigated, and our results show that lipophilicity and molecular size are significantly correlated with BSEP inhibition. This data set was further used to build predictive BSEP classification models through multiple quantitative structure-activity relationship modeling approaches. The highest level of predictive accuracy was provided by a support vector machine model (accuracy = 0.87, κ = 0.74). These analyses highlight the potential value that can be gained by combining computational methods with experimental efforts in early stages of drug discovery projects to minimize the propensity of drug candidates to inhibit BSEP.

Topics: Animals; ATP Binding Cassette Transporter, Subfamily B, Member 11; ATP-Binding Cassette Transporters; Bile Acids and Salts; Cell Line; Chemical and Drug Induced Liver Injury; Humans; Quantitative Structure-Activity Relationship

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60-70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the "Rule of Three" was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

Topics: Animals; Anti-Infective Agents; Anti-Inflammatory Agents; Chemical and Drug Induced Liver Injury; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Models, Biological; Predictive Value of Tests

Lennox-Gastaut syndrome (LGS) is a well-defined epileptic encephalopathy highly drug resistant. The first-line treatment option is valproate (VPA), usually in combination with lamotrigine. VPA has been linked to serious hepatotoxicity. We report a 22-year-old liver transplanted patient with LGS successfully treated with VPA in combination with phenobarbital (100 mg/d; blood level: 36 mg/l), lamotrigine (125 mg/d; blood level: 4.81 mg/l) and topiramtate (175 mg/d), as well as immunosuppressive, antiviral, anti-anemic, hypo-phosphoric and alkaline medication. On VPA 1000 mg/d, the seizure frequency decreased significantly. Taking into consideration the patient's good tolerance and the normal liver function, VPA was increased to 1500 mg/d. At this dose the daily drop attacks and generalized tonic-clonic seizures totally ceased. The patient presented only some tonic seizures around awakening. During many years, VPA was avoided in this patient because of its potential hepatotoxicity. However the good functioning of the transplanted liver permitted its introduction. VPA can be used safely in liver transplanted patients under the strict control of the hepatic function.

Topics: Anticonvulsants; Chemical and Drug Induced Liver Injury; Electroencephalography; Female; Fructose; Humans; Immunosuppressive Agents; Intellectual Disability; Lamotrigine; Lennox Gastaut Syndrome; Liver Function Tests; Liver Transplantation; Phenobarbital; Seizures; Spasms, Infantile; Topiramate; Triazines; Valproic Acid; Young Adult

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automate

Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship

Drug-induced liver injury (DILI) is one of the most important reasons for drug development failure at both preapproval and postapproval stages. There has been increased interest in developing predictive in vivo, in vitro, and in silico models to identify compounds that cause idiosyncratic hepatotoxicity. In the current study, we applied machine learning, a Bayesian modeling method with extended connectivity fingerprints and other interpretable descriptors. The model that was developed and internally validated (using a training set of 295 compounds) was then applied to a large test set relative to the training set (237 compounds) for external validation. The resulting concordance of 60%, sensitivity of 56%, and specificity of 67% were comparable to results for internal validation. The Bayesian model with extended connectivity functional class fingerprints of maximum diameter 6 (ECFC_6) and interpretable descriptors suggested several substructures that are chemically reactive and may also be important for DILI-causing compounds, e.g., ketones, diols, and α-methyl styrene type structures. Using Smiles Arbitrary Target Specification (SMARTS) filters published by several pharmaceutical companies, we evaluated whether such reactive substructures could be readily detected by any of the published filters. It was apparent that the most stringent filters used in this study, such as the Abbott alerts, which captures thiol traps and other compounds, may be of use in identifying DILI-causing compounds (sensitivity 67%). A significant outcome of the present study is that we provide predictions for many compounds that cause DILI by using the knowledge we have available from previous studies. These computational models may represent cost-effective selection criteria before in vitro or in vivo experimental studies.

Topics: Bayes Theorem; Chemical and Drug Induced Liver Injury; Humans; Ligands

Topics: Acute Disease; Adolescent; Chemical and Drug Induced Liver Injury; Female; Fructose; Humans; Migraine Disorders; Neuroprotective Agents; Topiramate

We describe four children with Dravet syndrome treated with the combination of valproic acid (VPA) and topiramate (TPM) who developed transient liver toxicity. The time-interval between fever, administration of acetaminophen, epileptic status and liver enzyme disturbances in our four cases suggests that accumulation of toxic acetaminophen-metabolites is possibly responsible for liver toxicity. If acetaminophen and its metabolites cause those liver problems in children treated with the combination of VPA and TPM, the advice to use acetaminophen for treating fever in children using this combination, should be changed. Only future clinical observations and research can solve this clinical dilemma.

Topics: Acetaminophen; Analgesics, Non-Narcotic; Anticonvulsants; Chemical and Drug Induced Liver Injury; Developmental Disabilities; Drug Therapy, Combination; Enzymes; Female; Fructose; Humans; Infant; Influenza, Human; Liver Function Tests; Male; Myoclonic Epilepsy, Juvenile; NAV1.1 Voltage-Gated Sodium Channel; Nerve Tissue Proteins; Sodium Channels; Syndrome; Topiramate; Valproic Acid

The authors report a 51-year-old women with pharmacoresistant partial epilepsy who tolerated well valproate monotherapy and in combination with several other antiepileptic drugs, but developed symptoms and signs of reversible hepatic failure under a combination of valproate and topiramate. Symptoms resolved after discontinuation of VPA. This case provides further anecdotal evidence that topiramate may increase the risk of liver failure when given in combination with other potentially hepatotoxic antiepileptic drugs.

Topics: Anticonvulsants; Chemical and Drug Induced Liver Injury; Drug Therapy, Combination; Epilepsies, Partial; Female; Fructose; Humans; Intracranial Aneurysm; Liver Function Tests; Middle Aged; Postoperative Complications; Topiramate; Valproic Acid

We present three children with severe therapy-refractory epilepsy who tolerated valproate (VPA) well in various combinations with other antiepileptic drugs (AEDs) but developed typical VPA side effects in combination with topiramate (TPM).. The clinical symptoms began with apathy in all three children; two of them also had hypothermia. Furthermore all children had elevated blood ammonia levels, one child in combination with increased liver transaminases and one with thrombocytopenia.. All children recovered completely after discontinuation of VPA or TPM.. TPM seems likely to enhance the risk of side effects usually attributed to VPA and not described in TPM monotherapy. Our case reports suggest that possible adverse effects of VPA should be given particular attention when VPA is combined with TPM.

Topics: Affective Symptoms; Anticonvulsants; Chemical and Drug Induced Liver Injury; Drug Therapy, Combination; Epilepsy; Female; Fructose; Humans; Hyperammonemia; Hypothermia; Infant; Liver; Liver Diseases; Male; Risk Factors; Thrombocytopenia; Topiramate; Transaminases; Valproic Acid

Topics: Adult; Anticonvulsants; Bipolar Disorder; Chemical and Drug Induced Liver Injury; Drug Therapy, Combination; Female; Fructose; Humans; Liver Function Tests; Topiramate