TY - JOUR
T1 - Phytocannabinoid drug-drug interactions and their clinical implications
AU - Silva, Daniela Amaral
AU - Pate, David W.
AU - Clark, Robert D.
AU - Davies, Neal M.
AU - El-Kadi, Ayman O. S.
AU - Löbenberg, Raimar
PY - 2020
Y1 - 2020
N2 - Cannabis is a plant with a long history of human pharmacological use, both for recreational purposes and as a medicinal remedy. Many potential modern medical applications for cannabis have been proposed and are currently under investigation. However, its rich chemical content implies many possible physiological actions. As the use of medicinal cannabis has gained significant attention over the past few years, it is very important to understand phytocannabinoid dispositions within the human body, and especially their metabolic pathways. Even though the complex metabolism of phytocannabinoids poses many challenges, a more thorough understanding generates many opportunities, especially regarding possible drug-drug interactions (DDIs). Within this context, computer simulations are most commonly used for predicting substrates and inhibitors of metabolic enzymes. These predictions can assist to identify metabolic pathways by understanding individual CYP isoform specificities to a given molecule, which can help to predict potential enzyme inhibitions and DDIs. The reported in vivo Phase I and Phase II metabolisms of various phytocannabinoids is herein reviewed, accompanied by a parallel in silico analysis of their predicted metabolism, highlighting the clinical importance of such understanding in terms of DDIs and clinical outcomes.
AB - Cannabis is a plant with a long history of human pharmacological use, both for recreational purposes and as a medicinal remedy. Many potential modern medical applications for cannabis have been proposed and are currently under investigation. However, its rich chemical content implies many possible physiological actions. As the use of medicinal cannabis has gained significant attention over the past few years, it is very important to understand phytocannabinoid dispositions within the human body, and especially their metabolic pathways. Even though the complex metabolism of phytocannabinoids poses many challenges, a more thorough understanding generates many opportunities, especially regarding possible drug-drug interactions (DDIs). Within this context, computer simulations are most commonly used for predicting substrates and inhibitors of metabolic enzymes. These predictions can assist to identify metabolic pathways by understanding individual CYP isoform specificities to a given molecule, which can help to predict potential enzyme inhibitions and DDIs. The reported in vivo Phase I and Phase II metabolisms of various phytocannabinoids is herein reviewed, accompanied by a parallel in silico analysis of their predicted metabolism, highlighting the clinical importance of such understanding in terms of DDIs and clinical outcomes.
KW - cannabinoids
KW - drug interactions
KW - metabolism
UR - https://hdl.handle.net/1959.7/uws:58166
U2 - 10.1016/j.pharmthera.2020.107621
DO - 10.1016/j.pharmthera.2020.107621
M3 - Article
SN - 0163-7258
VL - 215
JO - Pharmacology and Therapeutics
JF - Pharmacology and Therapeutics
M1 - 107621
ER -