Fixed Dosing of Leuprolide Acetate, a GnRH Agonist, in Children with Central Precocious Puberty: A Population Pharmacokinetic Justification

Abstract

Background

Central precocious puberty is the early onset of puberty due to premature activation of the hypothalamic-pituitary-gonadal axis, which can reduce adult height. Leuprolide, a gonadotropin-releasing hormone agonist, reduces gonadotropin secretion and is the standard treatment for central precocious puberty.

Objective

This study aimed to build a population model to describe the pharmacokinetics of a 3-month leuprolide acetate depot formulation in pediatric patients with central precocious puberty, evaluate covariate effects (age and weight) on leuprolide pharmacokinetics, and assess flat-dosing feasibility in pediatrics.

Methods

Samples from 48 patients (aged 1–10 years) were collected over 24 weeks following the administration of 11.25 and 30 mg of a leuprolide acetate 3-month depot formulation. A population pharmacokinetic model was developed using non-linear mixed-effects modeling (NONMEM). Covariate effects were tested using a forward inclusion and backward elimination approach and exploratory data analysis.

Results

A one-compartment model with immediate and delayed first-order absorption and proportional error model best described leuprolide pharmacokinetics in children. A transit compartment model characterized the delayed absorption. Apparent clearance and volume estimates were 181 L/day and 7.11 L, respectively, which were in alignment with those estimated in adult patients with prostate cancer. The immediate and delayed absorption rate constants were 0.441 day⁻¹ and 0.00879 day⁻¹, respectively. The number of transit compartments and the mean transit time were 3 and 34.1 days, respectively. No covariates significantly affected leuprolide pharmacokinetics.

Conclusions

The developed model adequately characterized leuprolide pharmacokinetics in pediatrics. No significant covariate effects were observed, supporting the use of a fixed leuprolide dose in pediatrics.

Clinical Trial Registration

NCT00635817, registered 13 March, 2008.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40272-025-00733-2.

Key Points

Leuprolide acetate, a gonadotropin-releasing hormone agonist, is an approved therapy for adults with advanced prostate cancer and is also an approved treatment for children with central precocious puberty.

Various long-acting formulations were designed for an intramuscular injection in adults based on the desired dosing schedule.

A population pharmacokinetic model was developed and demonstrated that the leuprolide acetate depot 3-month formulation can be used without weight-based or age-based dosing to treat central precocious puberty at doses of 11.25 or 30 mg in children.

Introduction

Precocious puberty is one of the more common conditions encountered in pediatric endocrinology practices [1]. Central precocious puberty (CPP) is a clinical syndrome characterized by the development of secondary sex characteristics in relation to activation of the hypothalamic-pituitary-gonadal axis [2]. The premature development of secondary sex characteristics is accompanied by accelerated linear growth and skeletal maturation at an abnormally early age, which can compromise an individual’s final adult height and potentially cause psychological distress [2]. CPP occurs before the age of 8 years in girls and 9 years in boys and is more common in girls [2]. The estimated CPP prevalence is 1 in 5000–10,000 individuals [3]. More recent observational studies conducted in diverse populations worldwide indicate that the actual prevalence may be substantially higher [4–7]. Significant increases in incidence have been observed among specific demographic subpopulations [4, 7].

Gonadotropin-releasing hormone (GnRH) analogs are the drugs of choice for the treatment of CPP and have replaced hormonal therapy of progestins and anti-androgens, which demonstrated limited therapeutic value [3]. Such agents overcome the pulsatile endogenous GnRH by maintaining constant serum levels of GnRH activity. The treatment goal is to arrest pubertal development and its associated psychosocial difficulties and preserve the adult height by reducing growth velocity or bone maturation [3, 8].

Leuprolide acetate, referred to from here as leuprolide, is a synthetic GnRH agonist with greater potency and a longer half-life than the endogenous GnRH. It is approved for treating children with CPP and has been the primary GnRH agonist used, although there are many different analogs with different routes of administration [9]. Leuprolide has a short half-life (~3 hours) and hence had to be given initially as daily injections [10]. However, longer-acting depot formulations have been subsequently developed to allow less frequent dosing, improving patient adherence and quality of life. The safety and efficacy of leuprolide monthly (7.5 mg) and quarterly (11.25 and 15 mg) intramuscular (IM) injections have been previously established in children with CPP [11, 12]. Nevertheless, starting doses of leuprolide differ across clinics. In Europe, lower doses are commonly used, whereas in the USA, higher doses are more prevalent [3, 8, 9, 11–13]. However, no population analysis has been performed to evaluate the effect of CPP patient intrinsic and extrinsic factors on leuprolide pharmacokinetics. This work aimed to assess the potential effects of patient demographics and other covariates on pediatric leuprolide pharmacokinetics to evaluate the appropriateness of flat dosing in pediatric patients.

Methods

Study Design

A total of 80 children, aged 1–10 years, with CPP participated in a randomized, open-label phase III study, comparing two strengths of the leuprolide 3-month depot formulation (Lupron Depot-PED^®; AbbVie Inc., North Chicago, IL, USA) 11.25 mg and 30 mg. Patients received a total of two IM injections of either 11.25 mg or 30 mg of leuprolide acetate depot administered 3 months apart (a total of 6 months of treatment). The first injection was administered on day 1, and the second injection was administered on month 3 (day 84). The study was conducted at 22 sites in the USA, including Puerto Rico (see Electronic Supplementary Material). The study reported herein was conducted in accordance with the International Council for Harmonisation (ICH) guidelines, applicable regulations, and guidelines governing clinical study conduct and the ethical principles that have their origin in the Declaration of Helsinki. Approval was granted by the institutional review boards of the individual study sites, and each participant provided written informed consent prior to enrollment. Additional details of this study were previously reported [11].

Leuprolide Sample Collection and Measurement

Blood samples for pharmacokinetic assessments were collected from a subset of 48 participants (24 participants for each dose). Samples were collected pre-dose (0 hour), 0.5 and 1 hour, and at 2, 4, 8, 12, and 24 weeks following the first leuprolide acetate depot injection. Plasma leuprolide concentrations were determined from a total of eight blood samples (2 mL each) collected across the study visits. Leuprolide plasma concentrations were determined using a validated assay that utilized liquid chromatography and tandem mass spectrometry at PPD (Richmond, VA, USA). The assay selectively measured leuprolide. The lower limit of quantitation (LLOQ) was 0.025 ng/mL when 0.5 mL of plasma was used [13]. Observations below LLOQ were imputed as half of LLOQ (0.0125 ng/mL), as previously described in method 5 (M5) to manage observations below the LLOQ [14]. With approximately 3.5% of observations below the LLOQ, little to no impact was anticipated, and no significant effect on the precision of the final parameter estimates was expected.

Population Pharmacokinetic Modeling

The leuprolide population pharmacokinetic model was developed using non-linear mixed-effects modeling implemented on NONMEM version 7.5 software (ICON Development Solutions, Ellicott City, MD, USA). The first-order conditional estimation method with interaction was used. Diagnostic graphics and exploratory analyses were performed using R (Version 4.2.3), Xpose4 package (version 4.3.2), and RStudio (version 4.3.2, R Foundation for Statistical Computing, Vienna, Austria). The Perl-based software Perlspeaks-NONMEM (version 5.4.0) was used to perform bootstrapping and visual predictive checks [15].

The population pharmacokinetic model development started with the construction of the base model, which included the structural pharmacokinetic model and models for the inter-individual variability and residual variability. Inter-individual variability was assumed to be log-normally distributed and modeled using an exponential error structure. Modeling of residual error using different error models (i.e., additive, proportional, and combined additive and proportional error) was explored. Covariate effects on pharmacokinetic parameters were explored graphically and statistically tested using the forward inclusion and backward elimination approach.

Base Pharmacokinetic Model

One-compartment and two-compartment pharmacokinetic models were evaluated. To characterize the multi-phase release profile of the microsphere-based sustained release leuprolide 3-month depot formulation, which consists of an initial ‘burst’ followed by a prolonged period of gradual release, different absorption models were explored (i.e., sequential zero-/first-order followed by delayed first-order absorption, and parallel first-order and zero-order absorption followed by delayed first-order absorption) [9, 13, 16, 17]. A delay in the absorption process was explored using lag time and transit compartment models [18, 19].

Development of the Covariate Model

Covariates screened for their possible effect on pharmacokinetic parameters included creatinine clearance, liver function markers (bilirubin, blood urea nitrogen, aspartate aminotransferase, alanine transaminase), age, sex, body weight, body surface area, and body mass index. Creatinine clearance and body surface area were calculated using the Cockcroft–Gault and Mosteller formulas [20, 21].

The impact of continuous covariates on pharmacokinetic parameters was explored using power models with the covariate scaled by the median value. Covariate modeling was performed using the forward inclusion (0.01 significance level, objective function values [OFVs] drop of 6.63 for a change of one degree of freedom) and backward-elimination approach (0.001 significance level, OFV increase of 10.83 for a change of one degree of freedom). Evaluation of the empirical Bayesian pharmacokinetic parameter estimates versus covariate plots as well as changes in the estimates of pharmacokinetic parameter variability and residual variability guided covariate modeling. Nested models were compared using the likelihood ratio test, while non-nested models were compared using the Akaike information criterion.

Model Assessment

Models were evaluated based on their goodness of fit to the data using the following criteria: (i) successful convergence of the estimation and covariance routines; (ii) significant drop in the OFV (−2 · log-likelihood) of more than 3.84, which approximates a p-value of <0.05 based on the assumption of a χ² distribution for the distribution of differences of the objective functions for two models differing by 1 degree of freedom; (iii) agreement in scatterplots of the population and individual predicted versus measured observations and the lack of systematic trends or patterns in scatterplots of conditional weighted residuals versus predicted observations and versus time; and (iv) precision of the parameter estimates. In addition, shrinkage in ETAs (individual random effects) was also evaluated [22].

The precision of the final model parameter estimates was assessed using both the asymptotic standard errors, obtained from the covariance routine in NONMEM, and the bootstrap confidence intervals. In bootstrapping, patients were randomly sampled with replacement from the dataset used in model development to obtain 500 datasets with the same number of patients as the original dataset. The final model was then fitted to each of these datasets, and the parameter estimates were compared with the estimates from the original dataset.

Model Qualification

During development, models were qualified by prediction-corrected visual predictive checks, where the final parameter estimates were used to simulate 1000 replicates of the observed dataset [15]. Both observations and the simulated data were normalized on the typical model prediction for the median independent variable in each bin to account for variation in sampling times and predictive covariates introduced by binning the observations. The median, 5th, and 95th percentile concentrations of the simulated datasets were then plotted against the original observations.

Results

A total of 293 plasma concentrations from 48 patients with CPP were analyzed. The demographic and clinical characteristics of the patient population included in the pharmacokinetic analysis are summarized in Table 1.

Table 1.

Summary of patient characteristics at baseline

Characteristics	Leuprolide acetate 3-month depot
	11.25 mg	30 mg
n	24	24
Age, years
Mean (SD) [range]	7.88 (1.4) [5–10]	7.75 (1.9) [1–10]
Body weight, kg
Mean (SD) [range]	38.2 (9.8) [21.6–62.1]	36.4 (12.1) [14.1–62.6]
Body mass index, kg/m2
Mean (SD) [range]	20.0 (3.7) [17.9–40.0]	19.1 (3.7) [11.6–42.6]
Body surface area, m2
Mean (SD) [range]	1.20 (0.2) [0.834–1.59]	1.16 (0.2) [0.598–1.61]
Sex, n (%)
Female	22 (91.7)	22 (91.7)
Race, n (%)
White	13 (54.2)	14 (58.3)
Black/African American	5 (20.8)	5 (20.8)
Other	6 (25.0)	5 (20.8)
Creatinine clearance, mL/min
Mean (SD) [range]	117 (31.6) [39.5–193]	107 (29.7) [64.1–162]

n number of participants, SD standard deviation

A one-compartment disposition model with sequential first-order absorption processes (immediate and delayed) and first-order elimination best described the data. The schematic of the structural pharmacokinetic model is illustrated in Fig. 1. Implementation of a delayed absorption phase via lag time produced poorer fits compared with the transit compartment, based on a graphical assessment of their ability to describe the data and OFV (42 points higher). The inclusion of immediate zero-order absorption improved the goodness of fit; however, parameters such as the duration of input for the zero-order absorption process could not be estimated well. The final model was parameterized in terms of absorption rate constants for the immediate and delayed absorption processes (K_a1 and K_a2, respectively), mean transit time (MTT), number of transit compartments (N), apparent clearance (CL/F), and apparent volume of distribution (Vd/F), where F is the bioavailability. Mean transit time is the average time leuprolide spends in each transit compartment (Fig. 1). The number of transit compartments was fixed due to insufficient data to estimate the parameter with good precision. The number of compartments was fixed at three based on a successful model run that adequately described the absorption phase in the model diagnostics but failed to describe other phases. The final model included between-subject variability on K_a1, K_a2, clearance (CL), volume (V), and MTT, as well as a proportional residual error model. The structural model of the final model is shown in the following equations:

$$K_{a1i}={\theta }_1\times e^{{\eta }_{1i}},\text{where}{\eta }_{1i}\sim N\left(0,{\omega }_{1,1}^2\right)$$

$$K_{a2i}={\theta }_2\times e^{{\eta }_{2i}},\text{where}{\eta }_{2i}\sim N\left(0,{\omega }_{2,2}^2\right)$$

$${\text{CL}}_i={\theta }_3\times e^{{\eta }_{3i}},\text{where}{\eta }_{3i}\sim N\left(0,,,{\omega }_{\text{3,3}}^2\right)$$

$$V_i={\theta }_4\times e^{{\eta }_{4i}},\text{where}{\eta }_{4i}\sim N\left(0,,,{\omega }_{\text{4,4}}^2\right)$$

$$N_i={\theta }_5,$$

$${\text{MTT}}_i={\theta }_6\times e^{{\eta }_{5i}},\text{where}{\eta }_{5i}\sim N\left(0,,,{\omega }_{\text{5,5}}^2\right)$$

$$K_{30i}=\frac{{\text{CL}}_i}{V_i}$$

$$K_{\text{tri}}=\frac{N_i+1}{{\text{MTT}}_i}$$

Fig. 1.

Illustration of the structure of the final pharmacokinetic model. CL clearance, F1 fraction of dose absorbed via immediate first-order process, F2 fraction of dose absorbed via delayed first-order process, K_a1 absorption rate constants for the immediate absorption processes, K_a2 absorption rate constants for the delayed absorption processes, K_TR transit rate between compartments

Differential equation (1):

$$\frac{\text{d}A_{\text{Depot}1j}^{}}{\text{d}{t}_j}=-K_{a1j}\times A_{\text{Depot}1j}^{}$$

Differential equation (2):

$$\frac{\text{d}A_{\text{Depot}2j}^{}}{\text{d}{t}_j}=\text{Dose}\times F_2\times K_{\text{tri}}\times \frac{{\left(K_{\text{tri}}\times t_{\text{ad}}\right)}^{N_i}\times e^{-K_{\mathit{tri}}\times t_{\mathit{ad}}}}{\sqrt[2]{2\pi \times N_i^{N_i+0.5}}\times e^{-N_i}}-K_{a2i}\times A_{\text{Depot}2j}^{}$$

Differential equation (3):

$$\frac{\text{d}{A}_{\text{Cent}j}}{\text{d}{t}_j}=K_{a1j}\times A_{\text{Depot}1j}^{}+K_{a2i}\times A_{\text{Depot}2j}^{}-K_{30i}\times A_{\text{Cent}j}$$

where K_a1i, K_a2i, CL_i, V_i, N_i, MTT_i, and K_tri represent Ka1, Ka2, CL, V, N, MTT, and K_TR in individual i, respectively. θ₁, θ₂, θ₃, θ₄, θ₅, and θ₆ are the population typical values for Ka1, Ka2, CL, V, N, and MTT, respectively. η_1i, η_2i, η_3i, η_4i, and η_5i are the individual random effects in individual i on Ka1, Ka2, CL, V, and MTT, respectively. They follow a normal distribution with a mean of 0 and a variance of ${\omega }_{1,1}^2$, ${\omega }_{2,2}^2$, ${\omega }_{3,3}^2$, ${\omega }_{4,4}^2$, and ${\omega }_{5,5}^2$, respectively. A_Depot1, A_Depot2, and A_Cent represent the amount of leuprolide in depot 1, depot 2, and central compartments, respectively. t_ad represents the time after dose. F2 represents the fraction of leuprolide absorbed via delayed absorption. The differential equations 1, 2, and 3 describe the change in the amount of leuprolide over time in depot 1, depot 2, and the central compartments, respectively. The first term of the differential equation (2), which describes the input from the transit compartments, was transformed to a logarithmic form to prevent numerical difficulties for a large N during the minimization of the model in NONMEM.

The residual unexplained variability was modeled using the following equation:

$$C_{\text{obs}ij}=C_{\text{pred}ij}\times \left(1+{\epsilon }_{1ij}\right)$$

$${\epsilon }_{1ij}\sim N\left(0,{\sigma }_{1,1}^2\right)$$

where C_obsij and C_predij represent observed and predicted concentration for individual i at time j, respectively. ε_1ij represents the proportional error for individual i at time j, respectively. ε_1ij follows a normal distribution with means of 0 and variances of ${\sigma }_{1,1}^2$.

In the covariates assessment, none of the covariates, including body size indices and age, was found to be significant. The relationship between body weight and age with pharmacokinetic parameters is shown in Fig. 2. The parameter estimates of the final model, along with the corresponding percentage relative standard errors, are summarized in Table 2. Basic goodness of fit to the observed concentration plots is shown in Fig. 3. Further assessment of the model using visual predictive checks showed close agreement of the 5th, 50th, and 95th quantiles of the prediction-corrected observations with the 95% confidence intervals of the corresponding quantiles of the prediction-corrected simulated data (see Fig. 4). This demonstrates the selected model’s ability to describe the central tendency and variability of the observed data.

Fig. 2.

Scatterplot of pharmacokinetic parameters (clearance [CL] and volume of distribution [V]) versus age and body weight. Circles are observations

Table 2.

Final population pharmacokinetic parameter estimates for leuprolide in children with central precocious puberty

Parameter	Original dataset	Bootstrap datasets
	Estimate (%RSE)	Median	5th–95th percentilesa
CL/F (L/day)	181 (34.9)	184	152–215
Vd/F (L)	7.11 (35.2)	6.97	5.37–8.73
Ka1 (day−1)	0.441 (7.81)	0.438	0.414–0.464
Ka2 (day−1)	0.00879 (29.6)	0.00892	0.00424–0.0196
FRAC (–)	0.920 (3.77)	0.919	0.866–0.940
MTT (day)	34.1 (8.89)	33.9	27.8–43.7
N	3 (FIXED)	3	–

Parameter	Estimate (%CV) [shrinkage, %]	Median	5th–95th percentilesa
IIV CL/F	0.163 (42.1) [15.8]	0.158	0.0597–0.339
Covariance of CL/F and Vd/F	0.127 (55.1)	0.127	0.00543–0.249
IIV Vd/F	0.323 (49.1) [14.4]	0.288	0.136–0.489
IIV Ka1	0.0217 (39.0) [21.2]	0.0194	0.00667–0.0332
IIV Ka2	0.432 (43.7) [19.3]	0.390	0.132–0.782
IIV MTT	0.0763 (56.6) [34.4]	0.0668	0.000314–0.160
Proportional residual error	0.132 (14.8)	0.132	0.102–0.166

% CV percentage coefficient of variation, % RSE percentage relative standard error, CL/F apparent clearance, FRAC fraction of dose absorbed via immediate first-order process, IIV inter-individual variability, K_a1 absorption rate constant for immediate process, K_a2 absorption rate constant for delayed process, N number of transit compartments, MTT mean transit time, V_d /F apparent volume of distribution

^aMedian and the 5th and 95th percentiles were obtained from the non-parametric bootstrap

Fig. 3.

Goodness-of-fit plots. Circles represent observations; the solid gray lines show the zero residual line (A and C) or the line of unity (B and D); the red dotted line is the locally weighted regression (LOESS) line. Conc. concentration

Fig. 4.

Prediction-corrected visual predictive check for the final model. Circles represent prediction-corrected observations, and shaded areas represent 95% confidence intervals of the 5th, 50th, and 95th percentiles of prediction-corrected simulated data. Black lines represent 5th (dashed), 50th (solid), and 95th (dashed) percentiles of the prediction-corrected observations. Some values may appear below the lower limit of quantitation/2 because of prediction correction

Discussion

To the best of our knowledge, this is the first report on the population pharmacokinetics of leuprolide or any other GnRH agonist in children. The model was developed using pharmacokinetic data from a randomized, multi-center, phase III clinical trial where patients with CPP (aged 1–10 years) were treated with a leuprolide acetate 3-month depot formulation for 6 months, followed by a post-treatment follow-up period for 12 weeks, and the option to enter an extension study (Table 1).

A one-compartment model best described the plasma concentration–time profiles of leuprolide in children with CPP. Distinguishing between a two-compartment model and a one-compartment model exhibiting flip-flop kinetics was not feasible because of the absence of intravenous data from children and the limited sampling during the short distribution phase. Similar to the previously developed pharmacokinetic model for the 6-month leuprolide depot formulation used in adult prostate cancer treatment [23], the pediatric pharmacokinetic model of the 3-month depot formulation included immediate and delayed absorption processes. Although both formulations are generally similar in composition, the specific chemical composition of the microspheres containing leuprolide determines whether the depot formulation releases leuprolide over 3 or 6 months, as the microspheres in the 6-month depot formulation are designed to degrade gradually and release leuprolide steadily over a longer period [24]. In both formulations, immediate and delayed first-order processes best described the absorption characteristics. In this model, most of the dose administered (92%) was absorbed early via the immediate absorption process. This is consistent with the reported pharmacokinetic profile of leuprolide acetate depot formulations, where a peak in plasma concentration occurs quickly after administration due to the early burst phase in absorption. This early phase was followed by maintenance at much lower concentrations during a later part of the dosing interval because of the prolonged release [9, 25–27]. Such a profile also aligns with the drug-release characteristics of the microspheres used in the 3-month depot formulation studied here [17, 28]. The delay in the absorption process was best characterized by using a transit compartment model, which describes drug absorption as a multiple-step process represented by a chain of pre-systemic compartments. The lag time and combined zero-order and first-order absorption models were tested, but neither was able to describe the absorption phase in the concentration–time profiles. The advantage of using a transit compartment model for absorption lies in providing a more gradual transition, offering a physiologically plausible description of the delay. Additionally, it is more stable compared to the lag-time model, allowing for the estimation of inter-individual variability in the delay. Although some shrinkage was observed in inter-individual variability on absorption parameters, it was within acceptable ranges [22].

Only 8% of the administered dose was absorbed via the delayed absorption process, which is consistent with the percentage from our previous model in adult patients with prostate cancer [23]. Differences were observed in the values of the transit compartment model parameter estimates between the model developed for adult patients with prostate cancer and the current one for pediatric patients with CPP. However, it is important to highlight that the formulation used in pediatric patients is a 3-month depot formulation. In contrast, the formulation given to adults has a longer dosing interval of 6 months. Our models estimate the MTT values to be 34.1 and 57.4 days for the 3-month and 6-month formulations, respectively. The number of transit compartments was 3 and 21.6 for the 3-month and 6-month formulations, respectively. These findings indicate that the duration of the delayed absorption phase was ~12-fold longer in the 6-month formulation compared with the 3-month formulation, aligning with the longer release profile of the 6-month depot formulation. Drug absorption is expected to be faster in adults compared with pediatric patients following an IM injection because adults have higher absolute blood flow to the site of injection owing to their larger muscle mass. However, previous reports have indicated that faster absorption of water-soluble drugs in neonates and young children compared with older children and adults is due to higher water content in their muscles, which could also have contributed to the longer delayed absorption in adults compared with pediatric patients [29–32].

Establishing a leuprolide pharmacokinetic model for pediatric populations enabled the assessment of intrinsic factors such as weight and age on key pharmacokinetic parameters, including CL/F, Vd/F, and absorption rate constants. Including such covariates as a basis for dosing, where appropriate, is desirable because it normalizes the drug exposure, and hence minimizes between-subject variability in therapeutic outcomes and dose-related adverse events [33]. This is of importance in the case of CPP treatment, as inadequate suppression of gonadotropin leads to continued secondary sexual characteristics and irreversible progression of bone age. However, unnecessarily high treatment doses are costly and may inhibit growth (through the suppression of endogenous growth hormone secretion) and reduce bone density during treatment [3, 34]. Reliable outcomes have been reported with the depot form of leuprolide acetate administered at a dose of 3.75 mg once every 28 days [12]. However, there is a variation among clinics regarding the starting dose of leuprolide acetate. Lower doses (3.75 mg, 80–120 mcg/kg/28 days) are used in European countries, while higher doses (7.5 mg, 200–300 mcg/kg/28 days) are administered in the USA [3, 8, 9, 11–13].

Consistently, the CL and V estimates from this model in children align with those estimated in adult patients with prostate cancer. In this analysis, the estimated population CL of leuprolide was determined to be 181 L/day, which is within the previously reported range (166–271 L/day) for patients with prostate cancer [9, 26]. This finding is also in agreement with the CL we previously reported [23]. Further, the V we report here (7.11 L) also aligns with earlier findings in patients with prostate cancer (8.53 L) [23], indicating similar pharmacokinetic properties across these studies.

The use of weight-based dosing versus fixed dosing of large molecules has been widely studied and debated [35–38]. Some studies have shown the effect of weight on large molecule clearances, justifying the use of weight-based dosing; however, for other molecules, no such effect has been found. Previously, leuprolide acetate was dosed in patients with CPP based on their age and weight. The population analysis presented herein shows that neither age nor weight affects leuprolide pharmacokinetic parameters, thereby supporting the fixed dose of leuprolide in children.

Conclusions

The pharmacokinetics of the 3-month leuprolide depot formulation (currently approved and marketed as Lupron Depot-PED) in pediatric patients were successfully characterized through non-linear mixed-effects modeling. This analysis revealed no clinically significant associations between the demographic covariates of age and weight and the drug’s disposition and elimination. This analysis endorses the use of a fixed leuprolide acetate dose in pediatric populations rather than weight-based or age-based dosing. This model can also be utilized for dose optimization and study design in future pediatric studies. Although the developed model demonstrated a solid predictive performance, the limited sample size and narrow age range are notable factors to consider before generalizing the results to broader clinical populations.

Supplementary Information

Below is the link to the electronic supplementary material.

Funding

AbbVie funded this study and participated in the study design, research, analysis, data collection, interpretation of data, review, and approval of the publication. All authors had access to relevant data and participated in the drafting, review, and approval of this publication. No honoraria or payments were made for authorship.

Declarations

Conflict of interest

Omar N. Al Yacoub, Ahmed H. Salem, and Nael M. Mostafa are employees of AbbVie and may hold AbbVie stock or options. Chay Ngee Lim is a former employee of AbbVie and may hold stock in the company.

Ethics approval

The study reported herein was conducted in accordance with the International Council for Harmonisation guidelines, applicable regulations, and guidelines governing clinical study conduct and the ethical principles that have their origin in the Declaration of Helsinki. Approval was granted by institutional review boards and independent ethics committees at participating institutions.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent for publication

Patients signed an informed consent form regarding publishing their data.

Availability of data and material

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Code availability

Not applicable.

Author contributions

All authors contributed to the study conception and design. Data collection and analysis were performed by CL, OA, AS, and NM. The first draft of the manuscript was written by CL and OA and all authors critically reviewedprevious versions of the manuscript. All authors read and approved the final manuscript.