Development and Verification of a Linked Δ 9-THC/11-OH-THC Physiologically Based Pharmacokinetic Model in Healthy, Nonpregnant Population and Extrapolation to Pregnant Women

Abstract

Conducting clinical trials to understand the exposure risk/benefit relationship of cannabis use is not always feasible. Alternatively, physiologically based pharmacokinetic (PBPK) models can be used to predict exposure of the psychoactive cannabinoid (-)-Δ⁹-tetrahydrocannabinol (THC) and its active metabolite 11-hydroxy-Δ⁹-tetrahydrocannabinol (11-OH-THC). Here, we first extrapolated in vitro mechanistic pharmacokinetic information previously quantified to build a linked THC/11-OH-THC PBPK model and verified the model with observed data after intravenous and inhalation administration of THC in a healthy, nonpregnant population. The in vitro to in vivo extrapolation of both THC and 11-OH-THC disposition was successful. The inhalation bioavailability (F_inh) of THC after inhalation was higher in chronic versus casual cannabis users (F_inh = 0.35 and 0.19, respectively). Sensitivity analysis demonstrated that 11-OH-THC but not THC exposure was sensitive to alterations in hepatic intrinsic clearance of the respective compound. Next, we extrapolated the linked THC/11-OH-THC PBPK model to pregnant women. Simulations showed that THC plasma area under the curve (AUC) does not change during pregnancy, but 11-OH-THC plasma AUC decreases by up to 41%. Using a maternal-fetal PBPK model, maternal and fetal THC serum concentrations were simulated and compared with the observed THC serum concentrations in pregnant women at term. To recapitulate the observed THC fetal serum concentrations, active placental efflux of THC needed to be invoked. In conclusion, we built and verified a linked THC/11-OH-THC PBPK model in healthy nonpregnant population and demonstrated how this mechanistic physiologic and pharmacokinetic platform can be extrapolated to a special population, such as pregnant women. SIGNIFICANCE STATEMENT: Although the pharmacokinetics of cannabinoids have been extensively studied clinically, limited mechanistic pharmacokinetic models exist. Here, we developed and verified a physiologically based pharmacokinetic (PBPK) model for (-)-Δ⁹-tetrahydrocannabinol (THC) and its active metabolite, 11-hydroxy-Δ⁹-tetrahydrocannabinol (11-OH-THC). The PBPK model was verified in healthy, nonpregnant population after intravenous and inhalation administration of THC, and then extrapolated to pregnant women. The THC/11-OH-THC PBPK model can be used to predict exposure in special populations, predict drug-drug interactions, or impact of genetic polymorphism.

Graphical abstract

Fig. 1.

General workflow of THC and 11-OH-THC PBPK model development and verification after intravenous and inhalation of THC in a healthy nonpregnant population.

Fig. 2.

Observed (Obs.) and PBPK model–predicted (Pred.) THC plasma or serum (A) AUC_0-t and (B) C_max after inhalation of THC. The final THC intravenous PBPK model predictions (A and B) used the NLME estimated absorption parameters (ka = 12 hour⁻¹ and F_inh = 0.22). The THC AUC_0-t and C_max for casual users was typically overpredicted, whereas the reverse was true for chronic users. This suggests that casual and chronic users require a lower and higher F_inh, respectively. (C) THC F_inh was optimized for chronic and casual users via manual adjustment in order for datasets to meet the success criteria for the THC inhalation PBPK model. The optimized average ± S.D. F_inh were 0.19 ± 0.14 and 0.35 ± 0.19 for casual and chronic users, respectively. Using these optimized THC F_inh, the PBPK model–predicted versus observed parameters for 11-OH-THC after inhalation of THC are shown in (D–H). (D) The predicted 11-OH-THC C_max was larger than that observed but typically within 2-fold of observed values. (E) Majority of the predicted 11-OH-THC AUC_0-t fell within 2-fold of the observed values. (F) The mean simulated 11-OH-THC to THC AUC_0-t ratios (M/P AUCR) were similar to the observed values, indicating that the 11-OH-THC final PBPK model performed well. (G) Since the THC F_inh was optimized for each dataset, majority of the THC predicted concentrations were within 2-fold of observed values. (H) Majority of the predicted 11-OH-THC concentrations after THC inhalation were within 2-fold of observed values, further indicating good performance of the 11-OH-THC PBPK model.

Fig. 3.

Sensitivity analyses were conducted to assess impact of various PBPK model parameters on THC and 11-OH-THC disposition. (A) Since THC has high CL that is blood flow limited, THC CL is not sensitive to alterations to THC CL_int or protein binding (fu_p and fu_inc). (B) Since THC is a highly lipophilic compound, V_ss is most sensitive to fu_p and changes in the distribution of THC into adipose. (C) The 11-OH-THC to THC AUC ratio (M/P AUCR) is sensitive to changes in 11-OH-THC formation (fm and THC CL_plasma), 11-OH-THC elimination (11-OH-THC CL_int), and fu_inc estimate but the M/P AUCR is not sensitive to change in THC CL_int.

Fig. 4.

PBPK model–predicted serum THC and 11-OH-THC (A) concentration-time profiles and (B) AUC_0-inf in nonpregnant (NP) and pregnant [T1 (GW = 12), T2 (GW = 26), T3 (GW = 40)] subjects after inhalation of THC. (C) PBPK model–predicted and observed maternal serum THC concentrations at delivery (GW = 40) after smoking cannabis. To note, each datum represents an observed value from a different subject. These data are from Blackard and Tennes, 1984 and they did not report the dose of THC used by the subjects. As such, simulations were run assuming a dose representative of the average THC content in cannabis in 1984 (see Materials and Methods section).