morphine and Chemical-and-Drug-Induced-Liver-Injury

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

Drug-induced liver injury is the most common cause of market withdrawal of pharmaceuticals, and thus, there is considerable need for better prediction models for DILI early in drug discovery. We present a study involving 223 marketed drugs (51% associated with clinical hepatotoxicity; 49% non-hepatotoxic) to assess the concordance of in vitro bioactivation data with clinical hepatotoxicity and have used these data to develop a decision tree to help reduce late-stage candidate attrition. Data to assess P450 metabolism-dependent inhibition (MDI) for all common drug-metabolizing P450 enzymes were generated for 179 of these compounds, GSH adduct data generated for 190 compounds, covalent binding data obtained for 53 compounds, and clinical dose data obtained for all compounds. Individual data for all 223 compounds are presented here and interrogated to determine what level of an alert to consider termination of a compound. The analysis showed that 76% of drugs with a daily dose of <100 mg were non-hepatotoxic (p < 0.0001). Drugs with a daily dose of ≥100 mg or with GSH adduct formation, marked P450 MDI, or covalent binding ≥200 pmol eq/mg protein tended to be hepatotoxic (∼ 65% in each case). Combining dose with each bioactivation assay increased this association significantly (80-100%, p < 0.0001). These analyses were then used to develop the decision tree and the tree tested using 196 of the compounds with sufficient data (49% hepatotoxic; 51% non-hepatotoxic). The results of these outcome analyses demonstrated the utility of the tree in selectively terminating hepatotoxic compounds early; 45% of the hepatotoxic compounds evaluated using the tree were recommended for termination before candidate selection, whereas only 10% of the non-hepatotoxic compounds were recommended for termination. An independent set of 10 GSK compounds with known clinical hepatotoxicity status were also assessed using the tree, with similar results.

Topics: Chemical and Drug Induced Liver Injury; Cytochrome P-450 Enzyme Inhibitors; Cytochrome P-450 Enzyme System; Decision Trees; Drug Evaluation, Preclinical; Drug-Related Side Effects and Adverse Reactions; Glutathione; Humans; Liver; Pharmaceutical Preparations; Protein Binding

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

The bile salt export pump (BSEP) is an efflux transporter, driving the elimination of endobiotic and xenobiotic substrates from hepatocytes into the bile. More specifically, it is responsible for the elimination of monovalent, conjugated bile salts, with little or no assistance from other apical transporters. Disruption of BSEP activity through genetic disorders is known to manifest in clinical liver injury such as progressive familial intrahepatic cholestasis type 2. Drug-induced disruption of BSEP is hypothesized to play a role in the development of liver injury for several marketed or withdrawn therapeutics. Unfortunately, preclinical animal models have been poor predictors of the liver injury associated with BSEP interference observed for humans, possibly because of interspecies differences in bile acid composition, differences in hepatobiliary transporter modulation or constitutive expression, as well as other mechanisms. Thus, a BSEP-mediated liver liability may go undetected until the later stages of drug development, such as during clinical trials or even postlicensing. In the absence of a relevant preclinical test system for BSEP-mediated liver injury, the toxicological relevance of available in vitro models to human health rely on the use of benchmark compounds with known clinical outcomes, such as marketed or withdrawn drugs. In this study, membrane vesicles harvested from BSEP-transfected insect cells were used to assess the activity of more than 200 benchmark compounds to thoroughly investigate the relationship between interference with BSEP function and liver injury. The data suggest a relatively strong association between the pharmacological interference with BSEP function and human hepatotoxicity. Although the most accurate translation of risk would incorporate pharmacological potency, pharmacokinetics, clearance mechanisms, tissue distribution, physicochemical properties, indication, and other drug attributes, the additional understanding of a compound's potency for BSEP interference should help to limit or avoid BSEP-related liver liabilities in humans that are not often detected by standard preclinical animal models.

Topics: Animals; ATP Binding Cassette Transporter, Subfamily B, Member 11; ATP-Binding Cassette Transporters; Biological Assay; Biological Transport; Cell Line; Cell Membrane; Chemical and Drug Induced Liver Injury; Cytoplasmic Vesicles; Drug Evaluation, Preclinical; Humans; Liver; Rats; Reproducibility of Results; Spodoptera; Transfection; Xenobiotics

We discuss an infant with MI secondary to cystic fibrosis, who was managed surgically by a double barrel ileostomy for mid - small bowel atresia and developed severe faecal impaction in the post - operative period. The faecal impaction was treated successfully with oral NAC and 0.2% NAC contrast enemas. The patient's liver function tests revealed a dramatic increase in transaminases and bilirubin contemporaneous with the administration of the enemas. The levels showed a spontaneous improvement after discontinuation. This is only the second reported case of hepatotoxicity secondary to NAC enemas in the literature. While our experience offers modest support for the use of NAC, its efficacy is not yet proven and paediatric surgeons using NAC in the enema form need to closely monitor liver function contemporaneous with this agent's administration and adjust their treatment accordingly.

Topics: Acetylcysteine; Chemical and Drug Induced Liver Injury; Cystic Fibrosis; Enema; Fecal Impaction; Free Radical Scavengers; Humans; Ileus; Infant, Newborn; Meconium