Modeling potential interactions between oral Gaucher disease treatment and investigational COVID-19 therapies

The global outbreak of COVID-19 has resulted in high morbidity and mortality. With the urgency to repurpose drugs to treat this new infection, potential drug-drug interactions have largely been ignored. Some of these repurposed therapies may share metabolic pathways with commonly used medications. The population pharmacokinetics (PopPK) approach to evaluate drug-drug interactions (DDI) can allow the study of probable interactions between these investigational drugs and approved orphan drugs for inherited metabolic disorders. The objective of this study is to elucidate potential pharmacokinetic DDIs involving eliglustat, a substrate reduction therapy (SRT) for Gaucher disease (GD) as an example. Eliglustat is the only first-line oral SRT available for the long-term treatment of patients with GD. It is primarily metabolized by CYP2D6, a genetically polymorphic enzyme, and to a lesser extent by CYP3A4. From a DDI standpoint, eliglustat can be a victim or a perpetrator. Current labeling information for eliglustat describes the DDI potential and its management from a ‘worst-case-scenario’ perspective. However, such information does not guide clinicians on the dosage adjustments that might be needed if the concomitant drug has mild or moderate induction or inhibition effect on CYP2D6 and/or CYP3A4. From literature-based eliglustat PopPK parameter estimates, covariate effects (e.g. genotype) and observed inter-individual variability, a PopPK model for eliglustat was constructed, and used to simulate concentration-time data in the patient population. Investigational COVID-19 drug effects were identified, and their uncontrolled concomitant use was incorporated into the model as covariates. This simulation study was performed using the R package mrgsolve in RStudio. Results of this analysis will be discussed. More broadly, in silico pharmacological evaluations using available information can be employed to characterize clinically important interactions between drugs to treat inherited metabolic disorders and other routinely prescribed drugs.