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\begin{document}

\title{Drug-Drug Interaction of Tacrolimus and Voriconazole in Pediatrics with
Different Age Groups Compared with Adults}



\author[1]{Meiling Zuo}%
\author[1]{Yuxuan Sun}%
\author[2]{Ailin Zhang}%
\author[1]{Jingtao Chen}%
\author[1]{Liqin Zhu}%
\affil[1]{Affiliation not available}%
\affil[2]{Tianjin Medical University}%


\vspace{-1em}



  
  \date{May 22, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Aim: To evaluate drug--drug interaction (DDI) between tacrolimus (TAC)
and different formulations of voriconazole (VRCZ) in adults and
pediatrics with different ages. Method: Physiologically based
pharmacokinetics (PBPK) models were used to evaluate DDI between oral
TAC and different formulations of VRCZ (oral and intravenous (IV)
formulations) in adults and pediatrics with different age groups. Both
single dose and multiple dose administration were assessed. Multiple
dosage regimens were maintained for 7 days. Result: A higher IV dose
might lead to a great increase in area under the plasma
concentration-time curve (AUC) and maximum concentrations (Cmax) of TAC
in both adults and pediatrics. Besides, compared with IV administration,
these two PK values of TAC increased more when combined with VRCZ
orally. The ratio of two PK values increased with the age growth in
pediatrics. And it increased progressively to adult values at the age of
3-8 years. Tacrolimus liposolubility was the most significant parameter
on the DDI between TAC and VRCZ. Conclusion: In pediatric population,
VRCZ had a less impact on PK of TAC than that in adults. The DDI
progressed gradually as the age advances in pediatrics and finally equal
to adults. Oral VRCZ increased PK parameters of tacrolimus even more
than IV administration. Personalized dosage adjustment should be
considered in clinical practice when co-administrated with VRCZ,
especially in adults or in oral formulation.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Tacrolimus (TAC) was a macrolide immunosuppressant, had proven to be of
immense utility in immunosuppression following organ transplant surgery
{[}1, 2{]}. Its use had revolutionized the future of immunosuppressive
regimens in solid organ transplantation and had been associated with
better graft survival, a lower incidence of rejection, and improved drug
tolerance with fewer side effects {[}3{]}. However, its monitoring
remained complicated and underexposure increaseed the risk of rejection,
whereas overexposure increased the risk of adverse effects, primarily
hepatotoxicity and infections {[}4{]}. The pharmacokinetic variability
of TAC complicated its daily dose assessment, potentially due to its
narrow therapeutic window, propensity for clinically drug--drug
interactions (DDI), patient age, hepatic dysfunction, concomitant
medications as well as interindividual variability in its
pharmacokinetic profile or disposition {[}5{]}. Among the potential
causes for large variability, the high inter-patient pharmacokinetic
variability of TAC, especially between adult and pediatric patients,
justified dose adjustment based on age grouping {[}6{]}.

Patients with immune compromise after solid organ transplantation were
at risk for serious fungal infections. First-line treatment commonly
consisted of the antifungal drug voriconazole (VRCZ) {[}7{]}. VRCZ was a
potent antifungal agent used for the treatment of invasive fungal
infections {[}8{]}. It had been reported that VRCZ inhibited the
metabolism of TAC and the blood concentration/dose ratio of TAC was
significantly correlated with the blood concentration of VRCZ when TAC
was intravenously administered {[}9, 10{]}. Administration of VRCZ to
TAC-treated adult patients resulted in a major DDI characterized by
increased exposure to TAC {[}9-11{]}. Therefore, therapeutic drug
monitoring (TDM) of TAC was essential when combined with VRCZ.

Despite the fact that clinical trials of TAC drug monitoring in organ
transplant recipients were reflected in many studies, detailed and
practical information on the interaction between TAC and VRCZ in
pediatric cases was still scarce. The evidence of association in
pediatric patients was not as extensive as adults {[}12{]}. Therefore,
the aim of the present study was to construct a physiologically based
pharmacokinetic (PBPK) model to quantify the DDI between TAC and
different formulations of VRCZ in adults and pediatrics with different
age groups. To overcome the large pharmacokinetic variability of TAC,
optimize efficacy and reduce toxicity, we provide strong insights into
the interaction between TAC exposure and VRCZ in pediatric patients and
compare it to adults. It could assist the clinical implementation of
precision medicine approaches to determine the factors that influence
appropriate dosing.

\textbf{Methods}

Study design

The PBPK modeling was conducted in PK-Sim\selectlanguage{ngerman}® (version 11.0, part of the
Open Systems Pharmacology suite), which has a system- and drug-dependent
component. The simulated trials were conducted in virtual healthy adult
and pediatric population groups. For adults, healthy volunteers between
18 and 60 years were selected. Virtual pediatric subjects were aged 0-18
years and divided into 5 groups: 0-1 years, 1-3 years, 5-8 years,
8-12years, 12-18 years. All simulations were performed with virtual
population of 100 individuals. The proportion of female was the default
0.5 in each simulation. Both p.o. and i.v. administration of VRCZ were
simulated in healthy adults and pediatrics.

PBPK model establishment and validation of TAC

General physiochemical properties (molecular weight, LogP, compound
type, pKa) of TAC and in vitro data from blood, plasma protein were
utilized for building the PBPK model {[}13-15{]}. System-dependent
physiological parameters (organ volumes, blood flow rates, hematocrit,
etc.) were provided in PK\selectlanguage{english}-Sim(r) with the small molecule model. The input
parameters for specific intestinal permeability were optimized using the
PK profiles of single 5mg TAC in healthy subjects. According to the
clinical routine drug regimens, a simulation of TAC was performed at a
single dosage of 2 mg for adults. The predictive performance was
evaluated by visually comparing predicted concentration-time data with
the observed data from the literature for initial verification

{[}16{]}. Predicted concentration-time profiles were obtained using the
developed PBPK model of TAC. Observed concentration--time data were
obtained in graphical form using GetData Graph Digitizer version
2.25.0.32. The ratio of predicted to observed pharmacokinetics (PK)
values was used to evaluate model performance. Next, the quantitative
assessment was conducted by calculating the mean fold error (MFE) of PK
parameters such as the area under the plasma concentration-time curve
(AUC) and maximum concentrations (Cmax), expressed as the ratio of
predicted to observed mean values. The model was acceptable if it met
the 0.5- to 2.0-fold limit. After model validation, the adult PBPK model
was scaled to children (pediatric PBPK model). Drug-specific parameters
defined in the adult PK data were kept constant for the pediatric PBPK
model. The physiological parameter values for pediatric individuals were
taken from the PK-Sim population database. The PBPK model performance in
pediatrics was evaluated using the quantitative verification described
in adult model verification{[}17{]}.

PBPK model establishment and validation of VRCZ

Drug-specific physicochemical properties were obtained from the
literature {[}18, 19{]}. Organ-plasma partition coefficients were
determined using Poulin and Theil's method based on the literature
{[}20{]}. The model was verified with clinical data of adults and
pediatrics in different formulations{[}21, 22{]}. The PBPK model
performance in children was evaluated using the quantitative
verification described in TAC model verification.

DDI simulations of TAC and VRCZ in adults and pediatrics

The DDI of TAC combined with VRCZ in different formulations and
different dosing regimens were simulated in adults and pediatrics.
Verified PBPK models were used to predict the DDI using PK-Sim(r). The
dosage and dosing interval of TAC and VRCZ were prescribed on the basis
of the clinical routine drug regimens. The detailed dosage regimens are
shown in Table 1. DDI simulations were performed in turn following these
dosing schedules.

Sensitivity Analysis

Sensitivity of the DDI between TAC and oral VRCZ to single parameters
(local sensitivity analysis) was calculated as relative change of AUC
using the Sensitivity Analysis tool implemented in PK-Sim(r). Sensitivity
analysis was performed applying a relative perturbation of 1000 \%
(variation range 10.0, maximum number of 9 steps). Parameters selected
for the sensitivity analysis fulfilled one of the

following criteria: (1) optimized; (2) related to optimized parameters;
(3) a strong influence in the model. Sensitivity to a parameter was
calculated as the ratio of the relative change of the simulated AUC to
the relative variation of the parameter around its value used in the
final model according to the Eq. (1):

\begin{equation}
S=\frac{AUC}{\text{AUC}}\bullet\frac{P}{P}\nonumber \\
 \end{equation}

where S = sensitivity of the simulated AUC0--24 to the examined model
parameter value, [?]AUC= change of the simulated AUC0--24, AUC = simulated
AUC0--24 with the original parameter value, [?]p = change of the examined
parameter value, p = original parameter value. A sensitivity value of
+1.0 means that a 10\% change in the examined parameter causes a 10\%
alteration of the predicted AUC.

\textbf{Results}

PBPK model and verification of TAC

The input parameters describing the PBPK model of TAC are listed in
Table 1. With the optimization of specific intestinal permeability, the
resulting TAC model was able to capture the PK profile of single 5mg TAC
dose in healthy volunteers (Supplement Figure 1). The simulated and
observed plasma concentration--time profiles of TAC are shown in Figure
1. There was a good match between predicted and observed data in both
adults and pediatrics. The predicted and observed PK parameters are all
summarised in Table 3. The accuracy of simulation was measured by
calculating the fold error between simulated and observed, described as
Eq. (1). Predicted PK parameters were reasonably consistent (0.5- to
2.0-fold) with observed clinical values which indicated that the
prediction accuracy of the developed PBPK models were acceptable and
could be used to simulate the different dosing regimens.

PBPK model and verification of VRCZ

The input parameters describing the PBPK model of TAC are listed in
Table 2. The simulated and observed plasma concentration--time profiles
of VRCZ are shown in Figure 2. Simulated plasma concentration--time
profiles of TAC in both adults and pediatrics corresponded well with the
observed profiles. The pharmacokinetic parameters of VRCZ were all
within 2.0-fold error (Table 3).

DDI simulations between TAC and VRCZ in adults and pediatrics

The plasma concentration--time curves of single oral TAC at baseline and
following both single IV and oral dose of VRCZ in adults and pediatrics
are shown in Figure 3. Model-predicted Cmax and AUC of TAC combined with
VRCZ (IV and oral) were obtained (supplement Table 1). These results
indicated that a higher IV dose might lead to a great increase in Cmax
and AUC of TAC in both adults and pediatrics. Besides, compared with IV
administration, these two PK values of TAC increased more when combined
with VRCZ orally. The ratio of Cmax and AUC

in multidose simulation (IV and oral) was presented in Figure 4. The
ratio of two PK values increased with the age growthin the pediatrics.
And it increased progressively to adult values at the age group of 3-8.

Sensitivity Analysis

A sensitivity analysis was performed based on the simulation of the
therapeutic single oral dosing regimen (TAC oral 0.05mg/kg and VRCZ oral
400mg) to assess the impact of the parameters on the DDI between TAC and
VRCZ. Sensitivity analysis (Figure 5) revealed that the DDI between TAC
and VRCZ was sensitive to the values of TAC liposolubility, VRCZ
liposolubility, TAC fraction unbound in plasma, CYP2C19 kcat and
reference concentrition , CYP3A4 kcat and km, as well as intestinal
permeability. The most impactful drug parameters in the model were TAC
liposolubility.

\textbf{Discussion}

This was the first study to explore the DDI between TAC and different
formulations of VRCZ in adults and pediatrics with different age groups
using PBPK models. The results indicated that IV and oral VRCZ both had
a significant effect on PK of TAC in two population. However, for
pediatrics at the age of 0-1, VRCZ presented a relatively unremarkable
effect on the PK of TAC compared with adults, and DDI was more
pronounced when VRCZ was administered orally. Besides, TAC
liposolubility was the most significant parameter on the DDI between TAC
and VRCZ.

Predicted values of the PBPK model established in this study were highly
close to the clinical observed values, indicating that the results
predicted by DDI model were credible. Firstly, it has shown that in
pediatrics at the age of 0-1, the DDI between TAC and VRCZ was
inapparent compared with adults. Besides, the DDI progressed gradually
as the age advanced and was finally equal to adults. That might be due
to enzyme inhibition of VRCZ was dose dependent{[}23{]}. Our study also
showed the same result that 6mg IV single dose showed more obvious
interaction compared with 4mg IV single dose. Pediatrics had faster
metabolism of VRCZ and lower accumulation of VRCZ than adults, and thus
the interaction in pediatrics was less pronounced than that in
adults{[}24{]}. Besides, many studies illustrated that compounds which
were mainly metabolized by CYP3A4 were likely to be mainly metabolized
by CYP3A7 in neonates and young infants{[}25-27{]}. The activity of
CYP3A4 was extremely weak or absent in the fetus and began to rise after
birth to reach 30--40\% of the adult activity after 1 month{[}28{]}.
There are also studies that show that CYP3A4 levels from the 5--15 year
age-group that were only 25\% of the average CYP3A4 value obtained from
the adult samples{[}29{]}. In our study, for the age dependent hepatic
clearance, default CYP3A4 ontogeny information was described in the
online PK-Sim Ontogeny Database Open Systems Pharmacology (2018). The
activity of CYP3A4 increased after birth and reached the adult level
over approximately 4 years. Therefore, the DDI in pediatrics at the age
of 3-8 years was basically at the same level compared with adults.

In the present study, it also illustrated that compared with IV
administration, both Cmax and AUC of TAC increased more when combined
with VRCZ orally. Previous research has also shown that the AUC of oral
midazolam increases by 885 \%, and the AUC of intravenous midazolam
increases by 261 \% on administration of 400 mg of oral VRCZ {[}30{]}.
The metabolism of TAC was known to be mainly mediated by CYP3A family,
which was most relevant in the intestinal and liver{[}31, 32{]}. In the
gut wall, members of the CYP3A sub-family are the predominant enzymes,
accounting for 82 \% of total intestinal CYP{[}23, 33{]}. Since VRCZ was
known to strongly inhibit CYP3A activity {[}34, 35{]}, oral VRCZ might
not only inhibit the metabolism of TAC in liver, but also inhibit the
absorption and transport of TAC in intestinal which could explain the
more prominent interaction when orally VRCZ{[}36{]}. Besides, there had
been some study illustrated that oral administration of VRCZ had a
stronger impact on CYP3A activity than intravenous administration. This
was expected because CYP-containing enterocytes would be exposed to
higher drug concentrations during duodenal and jejunal passage of orally
administered VRCZ compared with the lower concentrations reaching
enterocytes from the blood compartment{[}23{]}.

Finally, our study showed that TAC liposolubility was likely a most
contributing factor to the DDI between TAC and VRCZ. We also attempted
to simulate the DDI between TAC and VRCZ in different levels
liposolubility of TAC, and found that increasing the liposolubility of
TAC significantly reduced the degree of interaction with VRCZ. A rapid
initial distribution phase was followed by a plasma clearance phase
whose t1/2 depended on the physical chemistry characteristics of
drugs{[}37{]}. Lipid-soluble agents had lower plasma
concentrations{[}38-40{]}, perhaps because a more lipid soluble drug
might result in more-extensive tissue uptake, a larger volume of
distribution, lower plasma clearance values and a longer terminal
half-life{[}41{]}. This then could lead to a relatively less significant
interaction.

There were actually some limitations in our present study. Because of
the insufficient information of our existing population data, the object
of this study is only a virtual healthy population. The physiological
complications of transplant patients and changes during post-operative
period might affect the PK of TAC and VRCZ and influence their
interaction. In addition, previous researchers found that CYP2C19
polymorphism as a major metabolizing pathway of VRCZ might influence the
extent of drug interaction in healthy volunteers {[}42, 43{]}. Since
VRCZ blood concentrations in slow metabolizers of CYP2C19 may be higher
than fast metabolizers, which might result in more significant drug
interaction. The specific changes in CYP2C19 activity were not
considered in our models. The effects of CYP450 polymorphism on the
interaction and the specific changes in CYP2C19 activity would be
considered in our further researches.

\textbf{Conclusion}

An optimized PBPK model of TAC was successfully established in adults to
evaluate DDI between TAC and VRCZ with different administration.
Furthermore, the adult PBPK model had been successfully scaled to
pediatrics population with different age groups for assessment of DDI
between TAC and VRCZ. Both IV and oral VRCZ had a significant effect on
PK of TAC in two population. For pediatrics at the age of 0-1, VRCZ
presented a relative unremarkable effect on the PK of TAC compared with
adults, and DDI was more pronounced when VRCZ was administered orally.
The DDI progressed gradually as the age advances and finally equal to
adults. Besides, TAC liposolubility was the most significant parameter
on the DDI between TAC and VRCZ. In clinical practice, the concentration
monitoring and dosage adjustment of TAC should be emphasized when
co-administrated with VRCZ, especially in adult or in oral formulation.

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\textbf{Authorship:} Liqin Zhu provided ideas for the manuscript and
reviewed the manuscript; Meiling Zuo wrote the manuscript and analyzed
the data; Yuxuan Sun collected the data and analyzed data. Ailin Zhang
and Jingtao Chen contributed to validate the PBPK model; Liqin Zhu
provided a venue for research; All authors have approved the final
version of this manuscript.

\textbf{Funding:} All authors declare that no external funding has been
received.

\textbf{Disclosure statement:} The authors declare no conflicts of
interest.

\selectlanguage{english}\textbf{Data Availability Statement:} The data that support the
findings of this study are available from the corresponding author upon
reasonable request.

\textbf{Word count:} 2515

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\textbf{Hosted file}

\verb`Table.docx`  available at \url{https://authorea.com/users/459926/articles/619520-drug-drug-interaction-of-tacrolimus-and-voriconazole-in-pediatrics-with-different-age-groups-compared-with-adults}

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