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Article Abstract
Purpose: Nirmatrelvir/ritonavir (N/R) is the first drug to receive emergency authorization for the treatment of COVID-19 infection. We aimed to develop a population pharmacokinetic (PopPK) model to evaluate the effects of potential covariates and explore dosing regimen.
Patients And Methods: Sparse data of serum concentrations of N/R were obtained from 129 patients with COVID-19 infection receiving oral 300/100 mg N/R twice daily for 5 days. Plasma samples were assayed using ultra-high-performance liquid chromatography-tandem mass spectrometry. The PopPK model was developed using a nonlinear mixed effects approach utilizing the NONMEM 7.4 software. Monte Carlo simulation was conducted to optimize the dosage regimen.
Results: A one-compartment model with first-order absorption and first-order elimination provided the best fit for the data. Allometric scaling of parameters on creatinine clearance (CrCl) and body weight were identified as covariates that significantly influenced exposure-efficacy after oral administration of nirmatrelvir. Monte Carlo simulation using the final model generated concentration-time profiles for virtual patients (1,000 per group) with varying renal functions and body weight. Furthermore, we developed a web-based dashboard to visualize the dynamic changes in nirmatrelvir concentration and provide individualized dosage regimens.
Conclusion: This study showed that dosing regimen optimization of nirmatrelvir should be based on CrCl and body weight. Moreover, a web-based dashboard has been developed to facilitate individualized pharmacotherapy.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11622681 | PMC |
| http://dx.doi.org/10.2147/DDDT.S479561 | DOI Listing |
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