Bassma Eltanameli
University of Florida
Co-Authors: Sulafa Al Sahlawi1, Brian Cicali1, Rodrigo Cristofoletti1
1University of Florida
Background: Cannabidiol (CBD), a non-psychoactive component of cannabis, has gained significant attention for its therapeutic potential. Widespread legalization and weak regulation have led to its prevalent use, raising the risk of potential drug-drug interactions (DDIs) in people with comorbidities requiring multiple medications. In vitro studies showed that CBD and its active metabolite, 7-hydroxycannabidiol (7-OH-CBD), inhibit multiple Cytochrome P450 (CYP) enzymes via reversible and time-dependent inhibition (TDI). Our study aims to utilize physiologically based pharmacokinetic (PBPK) modeling to predict the extent of CBD-induced metabolic DDIs across multiple CYP enzymes in diverse populations.
Methods: Leveraging available in vitro and in vivo data on CBD and 7-OH-CBD, we developed a PBPK model using the Simcyp Simulator v.22. An intravenous (IV) model was built to describe CBD distribution and elimination, followed by an oral PBPK model validated against various single- and multiple-dose data. Model predictive performance was evaluated by comparing the ratios of predicted to observed PK parameter values, with an acceptance range of 0.5 to 2-fold. To explore the inhibitory effects of CBD, we simulated CBD co-administration with midazolam, caffeine, clobazam, and stiripentol. Verified in vitro interaction parameters for CYP3A4 and CYP2C19, and CYP1A2 were subsequently used to predict DDI magnitude in untested populations, including pediatrics, geriatrics, CYP2C19 poor metabolizers, obese, and hepatically impaired patients.
Results: The PBPK model successfully recapitulated CBD and 7-OH-CBD plasma concentration profiles following IV and oral administration in healthy adults and special populations, with predictions within twofold of observed values across various dosing regimens. Initial DDI simulations using in vitro inhibition parameters over- or under-predicted interactions. After parameter refinement, the model accurately predicted clinical DDIs, showing no significant interactions with midazolam, caffeine, or stiripentol. However, CBD increased the exposure of clobazam’s metabolite, N-desmethylclobazam, threefold due to CYP2C19 inhibition. This interaction remained consistent in pediatrics, geriatrics, and obese populations. Conversely, in hepatic impairment and CYP2C19 poor metabolizers, diminished enzyme activity led to a smaller relative impact of CBD’s inhibition.
Conclusions: Although CBD inhibited multiple CYP enzymes in vitro, this effect was not clinically evident except for a moderate CYP2C19 interaction risk, that was consistent across healthy, pediatric, geriatric, and obese populations. In vitro inhibition parameters may not reliably predict clinical DDI risk, emphasizing the need for caution when extrapolating in vitro data to clinical scenarios.