Background: Glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) are breakthrough medicines for obesity treatment and have rapidly gained widespread clinical application. Although GLP‐1RAs are generally not associated with drug–drug interactions (DDIs) via drug metabolism or transporter pathways, their effects on reduced gastrointestinal (GI) motility could influence the pharmacokinetics of coadministered oral medications. Objectives: This study uses physiologically based pharmacokinetic (PBPK) modeling to evaluate the DDI potential of GLP‐1RA‐induced GI motility delays. Methods: Using Certara's Simcyp™ Simulator V23, we modeled the pharmacokinetics of atorvastatin, metformin, metoprolol, ethinyl estradiol, and digoxin in a virtual cohort of obese adults ( n = 1000). GLP‐1RA‐related gastric emptying delays were simulated based on capsule endoscopy data from liraglutide‐treated patients. Results were compared with clinical data from semaglutide and liraglutide users. Additionally, exploratory analyses were conducted on frequently coadministered drugs identified from the 2022 Medical Expenditure Panel Survey, including rosuvastatin and dabigatran. Results: GLP‐1RA‐induced gastric emptying delays led to increased area under the concentration–time curve (AUC) and prolonged time to maximum concentration (Tmax) for several medications. The model outputs for rosuvastatin, valsartan, and dabigatran indicate increases in AUC by 64%, 90%, and 205%, respectively. Dabigatran, a narrow therapeutic index anticoagulant, exhibited the most significant changes, raising potential concerns of higher drug exposure. Conclusions: PBPK modeling suggests that GLP‐1RAs can influence the pharmacokinetics of oral medications by delaying gastric emptying, potentially leading to clinically relevant DDIs. While further clinical validation and pharmacovigilance is needed, these findings highlight the importance of PBPK tools in predicting and potentially mitigating risks associated with GLP‐1RA use.

Background Researchers have long been interested in the potential drug–drug interactions (DDIs) between opioids and benzodiazepines. However, much remains unknown concerning the interactions between these two drug classes. The objective of this work is to study the mechanism underlying the DDIs between opioids and benzodiazepines from the perspective of their pharmacokinetic (PK) interactions. A PK interaction occurs when two drugs are metabolized by the same cytochrome P450 enzymes and is one of the most common reasons for DDIs. Methods We quantitatively predicted the DDIs between three opioids (fentanyl, oxycodone and buprenorphine) and four benzodiazepines (alprazolam, diazepam, midazolam and triazolam) using a physiologically based pharmacokinetic (PBPK) modeling approach. A set of PBPK models was first constructed for these common opioids and benzodiazepines using SimCYP software, and the DDIs between them were then explored at various dosages. Results Our simulation results suggested there were no PK interactions between normal doses of opioids and benzodiazepines; but weak interactions can be expected with the combination of opioids and overdosed benzodiazepines. Particular attention should be given to the combination of fentanyl and overdosed alprazolam since a PK interaction can be observed between them. Conclusion Our results appear to indicate that pharmacodynamics may play a more important role than PKs in causing DDIs between opioids and benzodiazepines. This study also demonstrated that molecular modeling can be a very useful tool to mitigate the problem of “missing metabolic reaction parameters” in PK modeling and simulation.

ProTide technology is a powerful tool for the design of nucleoside/nucleotide analog prodrugs. ProTide prodrug design improves cell permeability and enhances intracellular activation. The hydrolysis of the ester bond of a ProTide is a determinant of the intracellular activation efficiency and final antiviral efficacy of the prodrug. The hydrolysis is dictated by the catalytic activity and abundance of activating enzymes. The antiviral agents tenofovir alafenamide (TAF) and sofosbuvir (SBV) are typical ProTides. Both TAF and SBV have also been proposed to treat patients with COVID-19. However, the mechanisms underlying the activation of the two prodrugs in the lung remain inconclusive. In the present study, we profiled the catalytic activity of serine hydrolases in human lung S9 fractions using an activity-based protein profiling assay. We evaluated the hydrolysis of TAF and SBV using human lung and liver S9 fractions and purified enzymes. The results showed that CatA and CES1 were involved in the hydrolysis of the two prodrugs in the human lung. More specifically, CatA exhibited a nearly 4-fold higher hydrolytic activity towards TAF than SBV, whereas the CES1 activity on hydrolyzing TAF was slightly lower than that for SBV. Overall, TAF had a nearly 4-fold higher hydrolysis rate in human lung S9 than SBV. We further analyzed protein expression levels of CatA and CES1 in the human lung, liver, and primary cells of the two tissues using proteomics data extracted from the literature. The relative protein abundance of CatA to CES1 was considerably higher in the human lung and primary human airway epithelial cells than in the human liver and primary human hepatocytes. The findings demonstrated that the high susceptivity of TAF to CatA-mediated hydrolysis resulted in efficient TAF hydrolysis in the human lung, suggesting that CatA could be utilized as a target activating enzyme when designing antiviral ester prodrugs for the treatment of respiratory virus infection.