DISCUSSION
In this study, the predictive performance of a published rFIX-Fc
population PK model was evaluated using independent real world
data16. The published model was based on patients ≥12
years whereas in this study children with age <12 years were
included as well. The published model significantly underpredicted the
observed FIX activity levels in all patients, especially for children
<12 years of age. Consequently, a new population PK model was
developed which should preferably be used to perform PK guided dosing in
young children.
Compared to the previously published model, our newly developed model
better describes the PK profiles of children <12 years of age
that were included. These improvements are not surprising as weight
normalized CL and V1 are generally larger in children compared to
adults12. This phenomenon has also been reported for
recombinant factor VIII-Fc fusion protein
(rFVIII-Fc)33. For children <12 years
specifically, the novel model shows adequate characterization of CL and
V1 (Fig. 2C and 2D).
Observed inter-patient variability of CL and V1, and within-patient
variability of CL were somewhat increased in comparison to reported
values (Table 2). As real word data is obtained from a highly
heterogenic population, a larger variability is imminent compared to
selected clinical study populations. This also explains why the residual
proportional error in the novel model (16.3%) was slightly higher
compared to the published model (10.6%) (Table 2). Real world clinical
data may contain more noise due to variability in assay precision,
variability in administration and sample times.
Surprisingly, this study found a near two-fold lower typical clearance
than reported by Diao et al.16 (Table 2). A possible
explanation for this may be related to the neonatal Fc receptor (FcRn),
to which the Fc domain of the IgG1 molecule in rFIX-Fc binds. FcRn
concentrations are negatively correlated with body
weight34. Consequently, children have higher
concentrations of weight-adjusted FcRn, possibly resulting in lower CL.
This is in contrast to the expected higher FIX CL in children, as is
found in factor VIII (FVIII)35,36. As half of our
population was paediatric (<18 years) and 38% was
<12 years of age, the age related effect on FcRn may have
influenced CL estimation.
Our real world clinical data was best described by a two-compartment
model and not by a three-compartment model as previously constructed by
Diao et al.16 This is due to differences in sampling
times during PK profiling between both study populations. More
specifically, the published model was constructed based on a rich
sampling schedule during a 10-day period, whereas the current study used
a maximum of six FIX activity levels sampled during a 7-day period. In
the present study, less FIX activity levels were sampled at early time
points. This could explain why we were not able to describe a third
compartment that characterizes the rapid distribution phase of rFIX-Fc
occurring within 2-3 hours after the end of
administration37. Notwithstanding these limitations,
our model adequately described the terminal elimination phase which
determines the trough concentration on which doses are generally
adjusted for in clinical practice.
The observed difference in terminal t1/2 between the
models is due to the difference in the estimated PK parameters.
Nevertheless, the t1/2 of the novel model (70, 76 and 88
h for <12 years, ≥12 and <18 years and adults,
respectively) are closer to the reported t1/2 in the
Alprolix® SmPC21 (70, 82 and 82 h) than those
calculated for the published model (88, 99 and 101 h).
In this study, we have illustrated the clinical impact of underlying
population PK models on dosing advice when personalizing treatment. In
general, a population PK model should be applied that is representative
for the patients for which individual PK are characterized. In our
study, however, we did not observe a difference in dose for patients
<12 years of age which could be due to the limited number of
patients. When considering data from all patients, a significant dose
difference was observed, probably caused by the difference in population
PK parameters.
In this context, it is important to realize that individual PK
parameters are calculated by combining information from both the
population and the individual. When more samples are available (5 or
more) per individual, individual PK parameters are mainly determined by
information from this individual. In the present study, an intermediate
clinically representative (3) number of samples was available, hence
individual PK parameters were mostly determined by the individual
observations. It should however be realized that large differences in
dose predictions may occur when less samples are available for an
individual patient.
The strength of the present study is that it contains real world data
reflecting clinical variability. A study limitation is the relatively
sparse sampling method with aforementioned consequences at early time
points. The impact of FIX extravascular distribution is recognized by a
growing body of literature and should be incorporated in future
models38–40. Investigation of extravascular binding
of FIX could be of clinical importance, as studies in mice suggest a
haemostatic function of extravascular FIX41,42. We,
carefully, advocate the use of other techniques, like physiology-based
pharmacokinetic (PBPK) models, to investigate an estimation of this
extravascular compartment.