Speaker
Description
Background: Escitalopram (S-CIT) is widely prescribed for depression and anxiety in older adults. A previous study indicated that the impact of CYP2C19 phenotypes on S-CIT pharmacokinetics is more pronounced in older adults than in younger individuals (Jang et al., Clin Pharmacol Ther 2025). This study quantified the risk of drug-drug interactions (DDIs) involving S-CIT in older and younger adults and in older adults with differing CYP2C19 phenotypes.
Methods: A physiologically-based pharmacokinetic (PBPK) model was developed using the Simcyp Simulator® (v.23) to predict the magnitude of CYP2C19-mediated DDIs in unstratified older and younger adults and in older adult sub-populations with varying CYP2C19 phenotypes. For DDI conditions, simulations were performed with S-CIT as the victim drug, co-administered with one of four CYP2C19 inhibitors (omeprazole, esomeprazole, fluconazole, and fluoxetine; selected based on a retrospective analysis of the 2019 Korean National Health Insurance Service senior cohort database). Additional simulations were performed to predict the pharmacokinetic changes of the four CYP2C19 inhibitors under DDI conditions.
Results: PBPK model-based simulations predicted a greater increase in systemic exposure of S-CIT in older adults than in younger adults, with varying magnitudes across CYP2C19 phenotypes (in the order of extensive, intermediate, and poor metabolizers). The simulations supported dose adjustment considerations not only for S-CIT but also for certain concomitant CYP2C19 inhibitors, based on their interaction potential in older adults.
Conclusions: These findings support CYP2C19 phenotype-guided dose adjustment for S-CIT in older adults. Implementing dose adjustment may reduce inappropriate medication use and the risk of adverse events in older adults.
