Discussion
In this study, popPK models for tezacaftor-ivacaftor and its active
metabolites were successfully developed in children with real-world data
using prior information from adolescent/adult models. Substantial
variability in AUC was observed both within and across age and dosing
groups. In general, AUC corresponded well with reported values in the
product information, except for tezacaftor in 12-17y and ivacaftor in
6-11y≥30kg. Cmax and half-lives also corresponded
closely with reported values, though in children 6-11y≥30kg
Cmax tended to be higher and in children
6-11y<30kg half-lives tended to be shorter. (3) Also, a strong
correlation between Cmin and AUC was found for
tezacaftor-ivacaftor.
Although in this study sparse data was available, the prior subroutine
was essential to successfully develop full popPK models, that also
described the absorption phase and the distribution to peripheral
compartments. It was not possible to obtain these extended models
without prior information, emphasizing the importance of prior
information in popPK modeling when data are limited, as is frequently
the case in pediatric studies. When data are sparse, there are two
methods to stabilize difficult-to-estimate parameters: 1. Fix them to a
previous value described in literature; 2. ‘Inform’ them about the
previous values. The latter strategy minimized bias in situations where
the parameters differed somewhat between the preceding population and
the population from which the sparse data were taken. (6)
The key covariate of relevance for this analysis was weight as predictor
of CL/F(*fm), Q/F(*fm) and
V/F(*fm), and was pre-defined. This is fairly typical in
pediatric studies due to the large weight range, partially explaining
the IIV in PK parameters. No other covariates explaining IIV were
identified, likely due to the study being underpowered for this type of
analysis. Interestingly, despite the real-world context, AUC variability
in our studies (CV=16-88%) was in close agreement with the reported
values in the product information. (3) A notable contribution of this
study is the first real-world AUC data for children in the 30-40 kg
weight class, as the registration studies relied on model-based
predictions in this weight group due to other weight-dose group
categorizations. (3, 5) Additionally, our findings of elevated AUC and
Cmax in children 6-11y≥30kg raise questions about
whether the tezacaftor-ivacaftor dose is appropriate for all children
within this subgroup, as they receive the adult dose. Lowering the dose
could reduce the risk of overexposure and possible development of side
effects, as well as saving costs. The observation of a consistent
relationship between Cmin and AUC in both this study and
our previous work in adults, suggests that Cmin could be
a valuable predictor of AUC for TDM in this population. (12)
This study benefits from several strengths, including the use of
real-world data in children 6-17y that allowed the analysis of AUC in
the 30-40 kg weight class, where limited data previously existed. Also,
real-world PK data are relevant to account for the difference between
controlled clinical trials and the complexity of drug use in diverse,
every day settings. Next, the selective use of informative prior
information from adolescents/adults was used to support portions of the
model that were not well defined from the currently available pediatric
data (Ka, D1, Vp, Q) and allowed for the estimation of
the remaining parameters (CL, V). Limited sampling strategies were
applied to reduce the burden of PK sampling in this age group. As well
as the use of DBS sampling (at home), which served as a feasible PK
sampling method and patients experienced this as less invasive than a
venipuncture. (8) Especially in the era of changing CF care this method
is preferable, as pwCF have better outcomes and will probably visit the
hospital less frequent. (13) Furthermore, intake with fatty food was
registered, which allowed for additional control over factors
influencing drug absorption as fatty food increases the absorption of
tezacaftor-ivacaftor. (3) Concomitant fatty food intake was not further
investigated in the covariate analysis, as the absorption parameters
were estimated with prior information and covariates can only be applied
on parameters estimated without priors. (6)
Despite this, the study has some limitations. The sample size was small,
due to faster access to ETI than expected, which limited the recruitment
as some children did not start with tezacaftor-ivacaftor awaiting ETI.
This also immediately implies that tezacaftor-ivacaftor is hardly used,
since the introduction of ETI. However, the findings in this study are
still useful because elexacaftor had little effect on the PK of
tezacaftor-ivacaftor, as indicated in the registration report. (4)
Furthermore, due to the short study duration, only one AUC curve was
acquired for certain patients who used home-based DBS collections. This
also resulted in incomplete covariate data in those patients (e.g.
liver-enzyme measurements), as they did not visit the hospital during
the study visit. This could have resulted in an underpowered covariate
analysis, prohibiting a thorough assessment of the IIV in PK of
tezacaftor-ivacaftor. This also made it impossible to assess the
inter-occasion variability. Last, self-reported adherence could have
influenced the results of the study, however this reflects a real-world
situation.
To conclude, this study is the first to describe the popPK of
tezacaftor-ivacaftor and its active metabolites in cwCF based on
real-world data. The selective use of prior information from
adolescent/adult models enabled the development of stable and robust
models. The popPK models developed in this study could be used as a
basis for more personalized medicine. Future applications of such TDM
models could enhance dose optimization, particularly for children
experiencing suboptimal efficacy, adverse effects, drug-drug
interactions, or where adherence is a concern.