orlistat and Chemical-and-Drug-Induced-Liver-Injury

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

Options for treating obesity remain limited despite it being a chronic, recurrent and morbid condition. New drugs that are proposed for its treatment encounter strong reluctance by regulatory agencies and many doctors.. This review will focus on the safety of an older drug, orlistat (the only one still approved in the European Union) and a newer recently FDA-approved one, lorcaserin. Both are approved as long-term monotherapy for obesity in the United States of America and they have demonstrated median weight loss of nearly 3% over placebo.. Research, development and approval of new anti-obesity drugs are necessary for improved management of this chronic condition. Orlistat and lorcaserin are two FDA-approved drugs with limited overall efficacy. Nevertheless they are useful weapons for at least some obese individuals. Orlistat has a long and solid safety profile, whereas the safety of lorcaserin is still a matter of debate, mainly due to a lack of long-term data. However, lorcaserin's selective agonism on 5HT2c serotonin receptors diminishes concerns about valvulopathy associated with other serotonin agonists, such as fenfluramine.

Topics: Anti-Obesity Agents; Benzazepines; Chemical and Drug Induced Liver Injury; Drug Interactions; Heart Valve Diseases; Humans; Lactones; Malabsorption Syndromes; Neoplasms; Orlistat; Serotonin Syndrome; United States; United States Food and Drug Administration

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 To better understand the association between BSEP interference and liver injury in humans, over 600 marketed or withdrawn drugs were evaluated in BSEP expressing membrane vesicles.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

To measure the association between orlistat and acute liver injury.. Self controlled case series study.. Population based primary care setting, United Kingdom.. 94,695 patients receiving orlistat and registered in the UK Clinical Practice Research Datalink and linked with Hospital Episode Statistics data between 1999 and 2011.. Relative incidence of acute liver injury comparing periods when patients were receiving orlistat with periods of non-usage.. Among 94,695 patients who received orlistat, 988 cases of acute liver injury were identified, with 335 confirmed as definite cases and 653 as probable cases. For all cases an increased incidence of liver injury was detected during the 90 day period before orlistat was first started, with an incidence rate ratio of 1.50 (95% confidence interval 1.10 to 2.06). The incidence remained raised during the first 30 days of treatment (2.21, 1.43 to 3.42), before returning to baseline levels with prolonged treatment. When the risk during the first 90 days of treatment was compared with the 90 days preceding first treatment, the incidence of liver injury was not increased (1.02, 0.67 to 1.56). An analysis restricted to definite cases showed no evidence of an increased risk of liver injury during treatment.. The incidence of acute liver injury was higher in the periods both immediately before and immediately after the start of orlistat treatment. This suggests that the observed increased risks of liver injury linked to the start of treatment may reflect changes in health status associated with the decision to begin treatment rather than any causal effect of the drug.

Topics: Adult; Anti-Obesity Agents; Case-Control Studies; Causality; Chemical and Drug Induced Liver Injury; Databases, Factual; Female; Humans; Incidence; Lactones; Male; Middle Aged; Obesity; Orlistat; Time Factors; United Kingdom

Topics: Anti-Obesity Agents; Canada; Chemical and Drug Induced Liver Injury; Databases, Factual; France; Humans; Kidney Diseases; Lactones; Obesity; Orlistat; Oxalates

Drug-induced liver injury (DILI) is a leading cause of drugs failing during clinical trials and being withdrawn from the market. Comparative analysis of drugs based on their DILI potential is an effective approach to discover key DILI mechanisms and risk factors. However, assessing the DILI potential of a drug is a challenge with no existing consensus methods. We proposed a systematic classification scheme using FDA-approved drug labeling to assess the DILI potential of drugs, which yielded a benchmark dataset with 287 drugs representing a wide range of therapeutic categories and daily dosage amounts. The method is transparent and reproducible with a potential to serve as a common practice to study the DILI of marketed drugs for supporting drug discovery and biomarker development.

Topics: Animals; Benchmarking; Biomarkers, Pharmacological; Chemical and Drug Induced Liver Injury; Drug Design; Drug Labeling; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmaceutical Preparations; Reproducibility of Results; United States; United States Food and Drug Administration

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

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

Topics: Adult; Anti-Obesity Agents; Chemical and Drug Induced Liver Injury; Female; Humans; Lactones; Liver Diseases; Orlistat

Orlistat(Xenical(R), Roche) is considered a safe and effective drug to treat obesity by reduced absorption of 30% digested fat. To date, no serious adverse effects affecting the liver have been published except a case of subacute hepatic failure leading to liver transplantation in a young women with moderate obesity treated with orlistat. We report a case of acute cholestatic hepatitis in a young woman with moderate obesity treated with orlistat: a 33-year-old female admitted for the evaluation of jaundice. Abdominal ultrasonography, ERCP, routine chemistry, viral markers, and a fine needle biopsy of liver were performed. Microscopic findings of the liver biopsy specimen were compatible with acute cholestatic hepatitis. After steroid therapy, liver function was improved.

Topics: Acute Disease; Adult; Anti-Obesity Agents; Chemical and Drug Induced Liver Injury; Cholestasis; Female; Humans; Lactones; Lipase; Orlistat

Topics: Acute Disease; Anti-Obesity Agents; Chemical and Drug Induced Liver Injury; Diagnosis, Differential; Female; Humans; Lactones; Metabolic Clearance Rate; Middle Aged; Obesity, Morbid; Orlistat