The use of the SAEM algorithm in MONOLIX software for estimation of population pharmacokinetic-pharmacodynamic-viral dynamics parameters of maraviroc in asymptomatic HIV subjects

Using simulated viral load data for a given maraviroc monotherapy study design, the feasibility of different algorithms to perform parameter estimation for a pharmacokinetic-pharmacodynamic-viral dynamics (PKPD-VD) model was assessed. The assessed algorithms are the first-order conditional estimation method with interaction (FOCEI) implemented in NONMEM VI and the SAEM algorithm implemented in MONOLIX version 2.4. Simulated data were also used to test if an effect compartment and/or a lag time could be distinguished to describe an observed delay in onset of viral inhibition using SAEM. The preferred model was then used to describe the observed maraviroc monotherapy plasma concentration and viral load data using SAEM. In this last step, three modelling approaches were compared; (i) sequential PKPD-VD with fixed individual Empirical Bayesian Estimates (EBE) for PK, (ii) sequential PKPD-VD with fixed population PK parameters and including concentrations, and (iii) simultaneous PKPD-VD. Using FOCEI, many convergence problems (56%) were experienced with fitting the sequential PKPD-VD model to the simulated data. For the sequential modelling approach, SAEM (with default settings) took less time to generate population and individual estimates including diagnostics than with FOCEI without diagnostics. For the given maraviroc monotherapy sampling design, it was difficult to separate the viral dynamics system delay from a pharmacokinetic distributional delay or delay due to receptor binding and subsequent cellular signalling. The preferred model included a viral load lag time without inter-individual variability. Parameter estimates from the SAEM analysis of observed data were comparable among the three modelling approaches. For the sequential methods, computation time is approximately 25% less when fixing individual EBE of PK parameters with omission of the concentration data compared with fixed population PK parameters and retention of concentration data in the PD-VD estimation step. Computation times were similar for the sequential method with fixed population PK parameters and the simultaneous PKPD-VD modelling approach. The current analysis demonstrated that the SAEM algorithm in MONOLIX is useful for fitting complex mechanistic models requiring multiple differential equations. The SAEM algorithm allowed simultaneous estimation of PKPD and viral dynamics parameters, as well as investigation of different model sub-components during the model building process. This was not possible with the FOCEI method (NONMEM version VI or below). SAEM provides a more feasible alternative to FOCEI when facing lengthy computation times and convergence problems with complex models

Pharmacokinetics of Oral Nirmatrelvir/Ritonavir, a Protease Inhibitor for Treatment of COVID-19, in Subjects With Renal Impairment

Nirmatrelvir coadministered with ritonavir is highly efficacious in reducing the risk of coronavirus disease 2019 (COVID-19) adverse outcomes among patients at increased risk of progression to severe disease, including patients with chronic kidney disease. Because nirmatrelvir is eliminated by the kidneys when given with ritonavir, this phase I study evaluated the effects of renal impairment on pharmacokinetics, safety, and tolerability of nirmatrelvir/ritonavir. Participants with normal renal function (n = 10) or mild, moderate, or severe renal impairment (n = 8 each) were administered a single 100-mg nirmatrelvir dose with 100 mg ritonavir given 12 hours before, together with and 12 and 24 hours after the nirmatrelvir dose. Systemic nirmatrelvir exposure increased with increasing renal impairment, with mild, moderate, and severe renal impairment groups having respective adjusted geometric mean ratio areas under the plasma concentration-time profile from time 0 extrapolated to infinite time of 124%, 187%, and 304% vs. the normal renal function group. Corresponding ratios for maximum plasma concentration were 130%, 138%, and 148%. Apparent clearance was positively correlated with estimated glomerular filtration rate, and geometric mean renal clearance values were particularly lower for the moderate (47% decrease) and severe (80% decrease) renal impairment groups vs. the normal renal function group. Nirmatrelvir/ritonavir exhibited an acceptable safety profile; treatment-related adverse events were mild in severity, and there were no significant findings regarding laboratory measurements, vital signs, or electrocardiogram assessments. These findings led to a dose reduction recommendation for nirmatrelvir/ritonavir in patients with moderate renal impairment (150/100 mg nirmatrelvir/ritonavir instead of 300/100 mg twice daily for 5 days). NCT04909853