Classic Histamine H1 Receptor Antagonists: A Critical Review of their Metabolic and Pharmacokinetic Fate from a Bird's Eye View

The so-called “classic” histamine H1 receptor antagonists are highly lipophilic compounds associated with significant biotransformation and tissue distribution. They are categorized according to their chemical structure into ethanolamines, alkylamines, ethylenediamines, piperazines, phenothiazines and piperidines, all of which have characteristic metabolic fates. The former four categories undergo primarily cytochrome P450-mediated oxidative Ndesalkylations and deamination whereas the aromatic rings of the latter two undergo P450-mediated oxidative hydroxylation and / or epoxide formation. The common tertiary amino group is susceptible to oxidative metabolism by flavin containing monooxygenases forming N-oxides, and the alicyclic tertiary amines produce small amounts (up to 7%) of N-glucuronides in humans. Species, sex and racial differences in the metabolism and pharmacokinetics of antihistamines are known. Specific P450-isozymes implicated in the metabolism were identified in a few cases, such as CYP2D6 that contributes to the metabolism of promethazine, diphenhydramine and chlorpheniramine. Low circulating plasma concentrations of antihistamines are in part explained by significant first-pass effect and tissue distribution. Antihistaminic effects last up to 6 hours though some compounds exhibit a longer duration of action due to circulating active metabolites. Importantly, diphenhydramine inhibited CYP2D6 leading to a clinically significant drug-drug interaction with metoprolol. Other classic antihistamines were shown to be potent in vitro inhibitors of CYP2D6 and CYP3A4. The prescription-free access to most classic antihistamines can easily lead to their co-administration with other drugs metabolized by the same enzyme system thereby leading to drug accumulation and adverse effects. In depth knowledge of the metabolic pathways of classic antihistamines and the enzymes involved is crucial to prevent the high incidence of drug interactions in humans, which are predictable based on pre-clinical data but unexpected when such data is unavailable.