Results
A total of 3540 pharmacokinetic records (99.1%) from 219 subjects (72
healthy volunteers and 147 HCV infection patients) were included for
model development. 31 (0.9%) samples below LLOQ were excluded from
analysis. All CWRES ranged between -6 and 6. No PK data points were
identified as outliers in the structural model and were excluded in the
process of model development. Baseline demographics and subject
characteristics were summarized in Table 2.
A two-compartment model with sequential zero-first order absorption and
first-order elimination was investigated to describe the
pharmacokinetics of yimitasvir. The structural model was first
established using intensive PK data from single ascending dose and
multiple ascending dose (CTR20140854, CTR20150048 and CTR20170932) in
healthy volunteers. A two-compartment model with first-order elimination
was superior to a one-compartment model to describe yimitasvir PK
profile. For the tested absorption model including first-order
absorption with or without a lag time, sequential zero-first order
absorption, transit absorption and saturable Michaelis-Menten
absorption, transit absorption model had the smallest AIC value and
fitted the data best from the goodness-of-fit plots. Sequential
zero-first order absorption model also performed well. When the full PK
data were used, transit absorption model converged difficultly and
slowly. Finally, we chose sequential zero-first order absorption model.
Residual variability was modeled by proportional error model.
After the base structural model was established, the dose effect on PK
parameters was tested first. The linear model was simple and adequate to
describe the effect of dose on bioavailability. With incorporation of
linear model, the objective function value (OFV) decreased by 82 units.
Model fitting was improved significantly especially for high
concentration data points. The typical value of Alpha was fixed to 0.129
according to the model result using data from SAD and MAD studies, which
indicated that the bioavailability of yimitasvir decreased 12.9% for
each 100 mg dose increase.
Subsequently, a stepwise forward inclusion and a backward exclusion
procedure were performed to screen different covariates. During
univariate screen procedure, covariates of ALT and AST, which were
highly correlated (r2 = 0.93), were statistically
significant on the same PK parameter of apparent clearance. ALT was
considered to be more significant (decrease in OFV 18.291) than AST
(decrease in OFV 12.675). As a result, the effect of ALT on clearance
was reserved for further covariate screening. Following the stepwise
forward inclusion process, food status was identified to be a
significant covariate on first-order absorption rate (Ka) and
bioavailability (F), gender and ALT were significant covariates on
apparent clearance and disease status on duration of zero-order
absorption (Td). None of these significant covariates was removed during
the process of backward elimination. The final model parameter
estimiates and their associated precisions (percent confidence of
variation, CV%), including the effect of significant covariates (P
< .001), were provided in Table 3. The typical values (for a
healthy male volunteer with ALT value of 31.6 IU l-1taking yimitasvir under fasted state) for apparent oral clearance (CL/F)
and central volume of distribution (V/F) were 13.8 l
h-1 and 188 l, respectively. Inter-individual
variability for CL/F and V/F and the covariance of them were 48.5%,
73.6% and 56.5%, respectively. The shrinkage values for CL/F and V/F
were 3.25% and 8.69%, respectively, which indicated that individual
empirical Bayes estimates PK parameters could be used to predict
yimitasvir exposures [13]. High-fat meal decreased Ka and F by
90.9% and 38.5%, respectively. Male subjects had a 22.2% higher
yimitasvir CL/F than females. Baseline ALT was another significant
covariate on apparent clearance. Duration of Zero-order absorption
duration was longer in healthy volunteers (2.17 h) than that in patients
(1.43 h). All the parameters were estimated with good precisions.
Goodness-of-fit plots for the final pharmacokinetic model are shown in
Figure 2. The population and individual predictions agreed with the
yimitasvir observations well, but there was a trend of under-prediction
at high concentration data points (Figure 2A and 2B). Most of these data
were from 200 mg group of phase 2 study. One possible assumption for the
bias was the lack of precise dosing history in phase 2 trial although
the last dosing time before each PK sampling was recorded. Most CWRES
ranged from y = ±4 and were evenly distributed at y = 0 (Figure 2C and
2D) with no obvious bias over the population predictions and time
indicating the proper choice of proportional model for the residual
variability.
Figure 3 shows the pcVPC plot stratified by study. The observed data
were evenly distributed around the median prediction and were mostly
within the 90% percentiles of the predicted concentrations, which
indicated that the model could adequately describe PK profile of
yimitasvir. In the bootstrap for the final model, all the 1000
replications ran successfully. The population parameter estimates were
close to the median values from bootstrapping analysis and fell within
95% confidence intervals (Table 3), suggesting that the final model was
robust and accurate.
The influence of significant covariates on predicted steady state
exposure (AUCss, Ctrough,ss and
Cmax,ss) was presented in Figure 4. The result revealed
that food status had a great impact on yimtasvir AUCssand Cmax,ss, but not Ctrough,ss.
AUCss and Cmax,ss decreased by 38.5%
and 58.9% after a high-fat meal, respectively. These results were
consistent with the result of the yimitasvir food effect study. The
Ctrough,ss of females was 54% higher than that of
males, while AUCss and Cmax,ss of
females were less than 30% higher than that of males. The magnitude of
ALT on the steady-state exposure of yimitasvir was mild
(~30%) for healthy volunteers with extreme ALT values
(5th and 95th percentiles) relative to the typical healthy volunteers.
There was no difference in exposures between patients and healthy
volunteers.