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Dexamethasone (DEX) is currently the treatment of choice for patients with oxygen-dependent COVID-19. It has been observed, primarily in vitro, that dexamethasone induces the expression of CYP3A and the ABCB1 gene, which encodes P-glycoprotein (P-gp). This has raised concerns about potential interactions between DEX and substrates of CYP3A and P-gp, such as direct oral anticoagulants (DOAC). Currently, there is limited robust evidence to support a clinically significant interaction between DEX and DOAC. Using physiologically based pharmacokinetic modeling (PBPK), we investigated the impact of DEX administered in the context of SARS-CoV-2 infection on the pharmacokinetics of apixaban (APX) and rivaroxaban (RVX). After validating the induction effect of the DEX compound on two CYP3A4 substrates using the limited available studies, we optimized the compound in a COVID-19 patient population, where significantly higher DEX plasma concentrations were observed compared to healthy volunteers. Our PBPK-based PK simulations showed a 20% decrease in the AUC of APX and RVX in a worst-case scenario and when DEX was administered at 6 mg PO for 10 days. This finding confirms the limited clinical data currently available and supports the use of APX and RVX with DEX in COVID-19 patients at low-risk for thrombo-embolism. In addition, our results suggest that prednisone (PRED), when used at an equipotent dose, could serve as a viable alternative to DEX, given its less pronounced induction effect on APX and RVX. Further research is needed to validate these findings and to explore the clinical implications of using PRED in place of DEX in such scenarios., (© 2024 The Author(s). Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

To compensate for drug response variability, drug metabolism phenotypes are determined based on the results of genetic testing, and if necessary, drug dosages are adjusted. In some cases, discrepancies between predicted and observed phenotypes (phenoconversion) may occur due to drug-drug interactions caused by concomitant medications. We conducted a prospective, exploratory study to evaluate the risk of CYP2C19 phenoconversion in genotyped healthy volunteers exposed to CYP2C19 inhibitors. Three groups of volunteers were enrolled: CYP2C19 g-RM, g-NM, and g-IM (g- for genetically predicted). All volunteers received as CYP2C19 phenotyping substrate 10 mg omeprazole (OME) alone at the control session and in co-administration with CYP2C19 inhibitors: voriconazole 400 mg and fluvoxamine 50 mg in second and third study sessions, respectively. Phenoconversion occurred in over 80% of healthy volunteers, with variations among genotypic groups, revealing distinct proportions in response to fluvoxamine and voriconazole. Statistically significant differences were observed in mean metabolic ratios between CYP2C19 intermediate metabolizers (g-IMs) with *1/*2 and *2/*17 genotypes, with the *2/*17 group exhibiting lower ratios, and distinctions were noted between genotypic groups, emphasizing the impact of genetic variations on drug metabolism. When reclassified according to CYP2C19 baseline-measured phenotype into p-RM, p-NM, and p-IM (p- for measured phenotype), we observed 100% phenoconversion of p-RMs and a significant phenotype switch in p-NMs, p-IMs, and p-PMs after fluvoxamine and voriconazole, and complete phenoconversion of p-IMs to p-PMs on both inhibitors, emphasizing the impact of genetic variations on the vulnerability to CYP2C19 phenoconversion and the importance of considering both genotyping and phenotyping in predicting drug response., (© 2024 The Author(s). Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)