Lamisil (terbinafine) toxicity: Determining pathways to bioactivation through computational and experimental approaches

Abstract

Lamisil (terbinafine) may cause idiosyncratic liver toxicity through a proposed toxicological mechanism involving the reactive metabolite 6,6-dimethyl-2-hepten-4-ynal (TBF-A). TBF-A toxicological relevance remains unclear due to a lack of identification of pathways leading to and competing with TBF-A formation. We resolved this knowledge gap by combining computational modeling and experimental kinetics of in vitro hepatic N-dealkylation of terbinafine. A deep learning model of N-dealkylation predicted a high probability for N-demethylation to yield desmethyl-terbinafine followed by N-dealkylation to TBF-A and marginal contributions from other possible pathways. We carried out steady-state kinetic experiments with pooled human liver microsomes that relied on development of labeling methods to expand metabolite characterization. Those efforts revealed high levels of TBF-A formation and first order decay during metabolic reactions; actual TBF-A levels would then reflect the balance between those processes as well as reflect the impact of stabilizing adduction with glutathione and other biological molecules. Modeling predictions and experimental studies agreed on the significance of N-demethylation and insignificance of N-denaphthylation in terbinafine metabolism, yet differed on importance of direct TBF-A formation. Under steady-state conditions, the direct pathway was the most important source of the reactive metabolite with a Vmax/Km of 4.0 pmol/min/mg protein/µM in contrast to model predictions. Nevertheless, previous studies show that therapeutic dosing leads to accumulation of desmethyl-terbinafine in plasma, which means that likely sources for TBF-A would draw from metabolism of both the major metabolite and parent drug based on our modeling and experimental studies. Through this combination of novel modeling and experimental approaches, we are the first to identify pathways leading to generation of TBF-A for assessing its role in idiosyncratic adverse drug interactions.