netilmicin and Chemical-and-Drug-Induced-Liver-Injury

We prospectively compared the efficacy and safety of netilmicin sulfate or tobramycin sulfate in conjunction with piperacillin sodium in 118 immunocompromised patients with presumed severe infections. The two treatment regimens were equally efficacious. Nephrotoxicity occurred in a similar proportion in patients treated with netilmicin and tobramycin (17% vs 11%). Ototoxicity occurred in four (9.5%) of 42 netilmicin and piperacillin and in 12 (22%) of 54 tobramycin and piperacillin-treated patients. Of those evaluated with posttherapy audiograms, three of four netilmicin and piperacillin-treated patients had auditory thresholds return to baseline compared with one of nine tobramycin and piperacillin-treated patients. The number of greater than or equal to 15-dB increases in auditory threshold as a proportion of total greater than or equal to 15-dB changes (increases and decreases) was significantly lower in netilmicin and piperacillin- vs tobramycin and piperacillin-treated patients (18 of 78 vs 67 of 115). We conclude that aminoglycoside-associated ototoxicity was less severe and more often reversible with netilmicin than with tobramycin.

Topics: Adult; Chemical and Drug Induced Liver Injury; Clinical Trials as Topic; Drug Therapy, Combination; Hearing Loss; Humans; Immune Tolerance; Infections; Middle Aged; Neoplasms; Netilmicin; Piperacillin; Prospective Studies; Random Allocation; Tobramycin

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