AIM: The severe psychiatric side effects of cannabinoid receptor type 1 (CB1 ) antagonists hampered their wide development but this might be overcome by careful management of drug development with pharmacokinetic/pharmacodynamic (PK/PD) analyses. PK/PD models suitable for direct comparison of different CB1 antagonists in Δ(9) -tetrahydrocannabinol (THC) challenge tests in healthy volunteer were constructed. METHODS: The pharmacokinetic models of THC and four CB1 antagonists were built separately. THC-induced effects on heart rate and the visual analogue scale of feeling high in healthy volunteers and inhibitive effects of CB1 antagonists on THC-induced effects were modelled in PD models linked to the PK models. Simulations were then applied to evaluate the reduction rate of each antagonist on the reversal of the THC-induced effect in a unified simulation scenario. RESULTS: The final PK model of THC and antagonists was a two compartment model. An Emax model and logistic regression model were used for effect measures and the antagonist effect was added in these models in a competitive binding manner. t1/2ke0 ranged from 0.00462 to 63.7 h for heart rate and from 0.964 to 150 h for VAS. IC50 ranged from 6.42 to 202 ng ml(-1) for heart rate and from 12.1 to 376 ng ml(-1) for VAS. Benchmark simulation showed different dose-efficacy profiles of two efficacy measures for each CB1 antagonist. CONCLUSIONS: PK/PD modelling and simulation approach was suitable for describing and predicting heart rate and feeling high for CB1 antagonists in THC challenge tests. Direct comparison of four antagonists based on simulated efficacy profiles might be of benefit to guide future studies.
AIM: The severe psychiatric side effects of cannabinoid receptor type 1 (CB1 ) antagonists hampered their wide development but this might be overcome by careful management of drug development with pharmacokinetic/pharmacodynamic (PK/PD) analyses. PK/PD models suitable for direct comparison of different CB1 antagonists in Δ(9) -tetrahydrocannabinol (THC) challenge tests in healthy volunteer were constructed. METHODS: The pharmacokinetic models of THC and four CB1 antagonists were built separately. THC-induced effects on heart rate and the visual analogue scale of feeling high in healthy volunteers and inhibitive effects of CB1 antagonists on THC-induced effects were modelled in PD models linked to the PK models. Simulations were then applied to evaluate the reduction rate of each antagonist on the reversal of the THC-induced effect in a unified simulation scenario. RESULTS: The final PK model of THC and antagonists was a two compartment model. An Emax model and logistic regression model were used for effect measures and the antagonist effect was added in these models in a competitive binding manner. t1/2ke0 ranged from 0.00462 to 63.7 h for heart rate and from 0.964 to 150 h for VAS. IC50 ranged from 6.42 to 202 ng ml(-1) for heart rate and from 12.1 to 376 ng ml(-1) for VAS. Benchmark simulation showed different dose-efficacy profiles of two efficacy measures for each CB1 antagonist. CONCLUSIONS: PK/PD modelling and simulation approach was suitable for describing and predicting heart rate and feeling high for CB1 antagonists in THC challenge tests. Direct comparison of four antagonists based on simulated efficacy profiles might be of benefit to guide future studies.
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