Cannabinoid use has surged in the past decade, with a growing interest in expanding cannabidiol (CBD) and delta-9-tetrahydrocannabinol (THC) applications into special populations. Consequently, the increased use of CBD and THC raises the risk of drug–drug interactions (DDIs). Nevertheless, DDIs for cannabinoids, especially in special populations, remain inadequately investigated. While some clinical trials have explored DDIs between therapeutic drugs like antiepileptic drugs and CBD/THC, more potential interactions remain to be examined. This review summarizes the published studies on CBD and THC–drug interactions, outlines the mechanisms involved, discusses the physiological considerations in pharmacokinetics (PK) and DDI studies in special populations (including pregnant and lactating women, pediatrics, older adults, patients with hepatic or renal impairments, and others), and presents modeling approaches that can describe the DDIs associated with CBD and THC in special populations. The PK of CBD and THC in special populations remain poorly characterized, with limited studies investigating DDIs involving CBD/THC in these populations. Therefore, it is critical to evaluate potential DDIs between CBD/THC and medications that are commonly used in special populations. Modeling approaches can aid in understanding these interactions.

The two most extensively studied cannabinoids, cannabidiol (CBD) and delta‐9‐tetrahydrocannabinol (THC), are used for myriad conditions. THC is predominantly eliminated via the cytochromes P450 (CYPs), whereas CBD is eliminated through both CYPs and UDP‐glucuronosyltransferases (UGTs). The fractional contributions of these enzymes to cannabinoid metabolism have shown conflicting results among studies. Physiologically based pharmacokinetic (PBPK) models for CBD and THC and for drug–drug interaction studies involving CBD or THC as object drugs were developed and verified to improve estimates of these contributions. First, physicochemical and pharmacokinetic parameters for CBD, THC, and their metabolites (7‐OH‐CBD, 11‐OH‐THC, and 11‐COOH‐THC) were obtained from the literature or optimized. Second, PBPK base models were developed for CBD and THC after intravenous administration. Third, beginning with the intravenous models, absorption models were developed for CBD after oral and oromucosal spray administration and for THC after oral, inhalation, and oromucosal spray administration. The full models well‐captured the area under the concentration–time curve (AUC) and peak concentration (C_max) of CBD and THC from the verification dataset. Predicted AUC and C_max for CBD and 7‐OH‐CBD were within two‐fold of the observed data. For THC, 11‐OH‐THC, and 11‐COOH‐THC, 100%, 100%, and 83% of the predicted AUC values were within two‐fold, respectively, of the observed values; 100%, 92%, and 94% of the predicted C_max values, respectively, were within two‐fold of the observed values. The verified models could be used to help address critical public health needs, including assessing potential drug interaction risks involving CBD and THC.