(T-006) Inhibitory Potential of Cannabidiol on Major CYP450s Enzymes: Insights from Physiological-based Pharmacokinetic Modeling

Bassma Eltanameli, MSc – PhD Student, Department of Pharmaceutics, University of Florida; Brian Cicali, PhD – Assistant Professor, University of Florida; Rodrigo Cristofoletti, PhD – Assistant Professor, Department of Pharmaceutics, University of Florida

Objectives: Patients prescribed medical marijuana often have multiple long-term medications, increasing their risk of drug-drug interactions (DDIs). In vitro, Cannabidiol (CBD) and its active metabolite, 7-Hydroxycannabidiol (7-OH CBD), are known to interact with CYP enzymes through reversible and time-dependent inhibition (TDI) [1]. Incorporation of their in vitro inhibition parameters into a mechanistic static model revealed that CBD could precipitate severe DDIs with substrates of CYP3A4 and CYP2C19, and moderate DDIs with drugs metabolized by CYP1A2 and CYP2C9 [1]. Our study aims to utilize physiologically based pharmacokinetic (PBPK) modeling to further explore CBD inhibitory potential on CYP450s.

Methods: Using the Simcyp Simulator (Version 22), we developed an intravenous (IV) PBPK model to characterize CBD distribution and elimination. We then constructed an oral PBPK model for CBD and 7-OH-CBD following single- and multiple-dose regimens. To explore the inhibitory effects of CBD on CYP3A4 and CYP2C19, we simulated CBD co-administration with Midazolam and Caffeine, respectively. Additionally, an independent PBPK model was developed for Clobazam and its metabolite N-desmethylclobazam to further assess the impact of CBD on CYP2C19 and CYP3A4 activity. 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.

Results: The base model recapitulated the plasma concentration profile observed after IV administration, achieving predicted to observed ratios close to 1. The oral PBPK model recapitulated the systemic exposure of CBD and 7-OH CBD in healthy adults within twofold of the observed values across single- and multiple-dose administrations and various dose levels. By fitting in vitro inhibition parameters to observed data, the model accurately predicted clinical DDI studies, confirming that CBD does not cause clinically significant interactions with midazolam (AUCR = 1.04) or caffeine (AUCR = 1.92). On the other hand, in vitro inhibition data successfully captured the observed clinical DDI when CBD was co-administered with Clobazam, resulting in a threefold increase in the exposure of N-desmethylclobazam due to CYP2C19 inhibition.

Conclusions: While CBD exhibits inhibitory effects on major CYP enzymes in vitro, these effects are not observed clinically, except for moderate CYP2C19 inhibition. DDI signals identified by mechanistic static models often overpredicted the risk of DDI. Further optimization of in vitro DDI parameters is often needed to capture clinical data. This highlights the challenges and uncertainties in scaling drug properties from in vitro studies to human predictions, emphasizing the need for caution when using in vitro data to predict DDIs. The validated PBPK model will be extended to simulate real-world scenarios, including the impact of age, food, CYP2C19 genotype, and hepatic impairment on the magnitude of DDIs.

Citations: [1] Bansal S, Maharao N, Paine MF, Unadkat JD. Predicting the Potential for Cannabinoids to Precipitate Pharmacokinetic Drug Interactions via Reversible Inhibition or Inactivation of Major Cytochromes P450. Drug Metab Dispos. 2020;48(10):1008-1017. doi:10.1124/dmd.120.000073