Population Pharmacokinetics and Dosing Regimen Analysis of Nirmatrelvir in Chinese Patients with COVID-19 Infection

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.

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.

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.

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.