Odalasvir

This study presents the case of a 19-year-old woman who attempted suicide by ingesting 11.25 g of venlafaxine (V). She was admitted to the hospital with severe biventricular dysfunction, progressing to cardiac arrest requiring extracorporeal circulatory life support for 11 days. The pharmacokinetics of venlafaxine during impaired cardiac output and the effect of its active metabolite, the O-desmethylvenlafaxine (ODV), are currently not very well understood.

Serum concentrations of V and ODV were monitored twice daily for 3 weeks. The maximum concentrations of venlafaxine and ODV were at 14 hours after ingestion, with 29,180 mcg/L for V and 5399 mcg/L for ODV. Half-lives increased, requiring 2 weeks to eliminate the drug. The left ventricular ejection fraction significantly improved when V + ODV was below 1000 mcg/L and remained altered until the ODV concentrations were lower than 400 mcg/L.

This report, with complete elimination kinetic of V and ODV in a monodrug intoxication, provides information about the modification of pharmacokinetics in the case of an overdose managed by extracorporeal circulatory life support, the cardiac toxicity of ODV, and the value of the toxic threshold for the active moiety.

Venlafaxine (VEN) is a commonly utilized medication for alleviating depression and anxiety disorders. The presence of genetic polymorphisms gives rise to considerable variations in plasma concentrations across different phenotypes. This divergence in phenotypic responses leads to notable differences in both the efficacy and tolerance of the drug.

A physiologically based pharmacokinetic (PBPK) model for VEN and its metabolite O-desmethylvenlafaxine (ODV) to predict the impact of CYP2D6 and CYP2C19 gene polymorphisms on VEN pharmacokinetics (PK).

The parent-metabolite PBPK models for VEN and ODV were developed using PK-Sim^® and MoBi^®. Leveraging prior research, derived and implemented CYP2D6 and CYP2C19 activity score (AS)-dependent metabolism to simulate exposure in the drug-gene interactions (DGIs) scenarios. The model's performance was evaluated by comparing predicted and observed values of plasma concentration-time (PCT) curves and PK parameters values.

In the base models, 91.1%, 94.8%, and 94.6% of the predicted plasma concentrations for VEN, ODV, and VEN + ODV, respectively, fell within a twofold error range of the corresponding observed concentrations. For DGI scenarios, these values were 81.4% and 85% for VEN and ODV, respectively. Comparing CYP2D6 AS = 2 (normal metabolizers, NM) populations to AS = 0 (poor metabolizers, PM), 0.25, 0.5, 0.75, 1.0 (intermediate metabolizers, IM), 1.25, 1.5 (NM), and 3.0 (ultrarapid metabolizers, UM) populations in CYP2C19 AS = 2.0 group, the predicted DGI AUC_0-96 h ratios for VEN were 3.65, 3.09, 2.60, 2.18, 1.84, 1.56, 1.34, 0.61, and for ODV, they were 0.17, 0.35, 0.51, 0.64, 0.75, 0.83, 0.90, 1.11, and the results were similar in other CYP2C19 groups. It should be noted that PK differences in CYP2C19 phenotypes were not similar across different CYP2D6 groups.

In clinical practice, the impact of genotyping on the in vivo disposition process of VEN should be considered to ensure the safety and efficacy of treatment.