Concerning the antiepileptic drugs which alter thyroid hormone homeostasis, it is highly probable that the mechanism of induction of uridine diphosphate glucuronosyltransferases (UGT) is involved, at least partially, in such an alteration. However, it is not possible to estimate the relative contribution of the UGT induction by these drugs on the total alteration observed in thyroid hormone levels, as other mechanisms not investigated, or not examined in the present article, could contribute.

In the field of gene expression analysis, DNA microarray technology is having a major impact on many different areas including toxicology. For instance, a number of studies have shown that transcription profiling can generate the information needed to assign a compound to a mode-of-action class. In this study, we investigated whether compounds inducing similar toxicological endpoints produce similar changes in gene expression. In vitro primary rat hepatocytes were exposed to 11 different hepatotoxicants: acetaminophen, amiodarone, clofibrate, erythromycin estolate, isoniazid, alpha-naphtylylisothiocyanate, beta-naphtoflavone, 4-pentenoic acid, phenobarbital, tetracycline, and zileuton. These molecules were selected on the basis of their variety of hepatocellular effects observed such as necrosis, cholestasis, steatosis, and induction of CYP P450 enzymes. We used a low-density DNA microarray containing 59 genes chosen as relevant toxic and metabolic markers. The in vitro gene expression data generated in this study were generally in good agreement with the literature, which mainly concerns in vivo data. Furthermore, gene expression profiles observed in this study have been confirmed for several genes by real-time PCR assays. All the tested drugs generated a specific gene expression profile. Our results show that even with a relatively limited gene set, gene expression profiling allows a certain degree of classification of compounds with similar hepatocellular toxicities such as cholestasis, necrosis. The clustering analysis revealed that the compounds known to cause steatosis were linked, suggesting that they functionally regulate similar genes and possibly act through the same mechanisms of action. On the other hand, the drugs inducing necrosis and cholestasis were pooled in the same cluster. The drugs arbitrarily classified as the CYP450 inducers formed individual clusters. In conclusion, this study suggests that low-density microarrays could be useful in toxicological studies.

In this article, aspects of absorption, distribution, metabolism, and excretion have been described bearing in mind the pathogenesis of allergic diseases and their possible therapeutic opportunities. The importance of the routes of administration of the different therapeutic groups has been emphasized. The classical aspects of drug metabolism and disposition related to oral administration have been reviewed, but special emphasis has been given to intranasal, cutaneous, transdermal, and ocular administration as well as to the absorption and the subsequent bioavailability of drugs. Drug-metabolizing enzymes and transporters present in extrahepatic tissues, such as nasal mucosa and the respiratory tract, have been particularly discussed. As marketed antiallergic drugs include both racemates and enantiomers, aspects of stereoselective absorption, distribution, metabolism, and excretion have been discussed. Finally, a new and promising methodology, microdosing, has been presented, although it has not yet been applied to drugs used in the treatment of allergic diseases.

No abstract

Drugs for allergy are often taken in combination with other drugs, either to treat allergy or other conditions. In common with many pharmaceuticals, most such drugs are subject to metabolism by P450 enzymes and to transmembrane transport. This gives rise to considerable potential for drug-drug interactions, to which must be added consideration of drug-diet interactions. The potential for metabolism-based drug interactions is increasingly being taken into account during drug development, using a variety of in silico and in vitro approaches. Prediction of transporter-based interactions is not as advanced. The clinical importance of a drug interaction will depend upon a number of factors, and it is important to address concerns quantitatively, taking into account the therapeutic index of the compound.