Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors

Abstract

Background: Atezolizumab has been studied in multiple indications for both pediatric and adult patient populations. Generally, clinical studies enrolling pediatric patients may not collect sufficient pharmacokinetic data to characterize the drug exposure and disposition because of operational, ethical, and logistical challenges including burden to children and blood sample volume limitations. Therefore, mechanistic modeling and simulation may serve as a tool to predict and understand the drug exposure in pediatric patients. Objective: To use mechanistic physiologically-based pharmacokinetic (PBPK) modeling to predict atezolizumab exposure at a dose of 15 mg/kg (max 1,200 mg) in pediatric patients to support dose rationalization and label recommendations. Methods: A minimal mechanistic PBPK model was used which incorporated age-dependent changes in physiology and biochemistry that are related to atezolizumab disposition such as endogenous IgG concentration and lymph flow. The PBPK model was developed using both in vitro data and clinically observed data in adults and was verified across dose levels obtained from a phase I and multiple phase III studies in both pediatric patients and adults. The verified model was then used to generate PK predictions for pediatric and adult subjects ranging from 2- to 29-year-old. Results: Individualized verification in children and in adults showed that the simulated concentrations of atezolizumab were comparable (76% within two-fold and 90% within three-fold, respectively) to the observed data with no bias for either over- or under-prediction. Applying the verified model, the predicted exposure metrics including C_min, C_max, and AUC_tau were consistent between pediatric and adult patients with a geometric mean of pediatric exposure metrics between 0.8- to 1.25-fold of the values in adults. Conclusion: The results show that a 15 mg/kg (max 1,200 mg) atezolizumab dose administered intravenously in pediatric patients provides comparable atezolizumab exposure to a dose of 1,200 mg in adults. This suggests that a dose of 15 mg/kg will provide adequate and effective atezolizumab exposure in pediatric patients from 2- to 18-year-old.

Keywords: alveolar soft part sarcoma; atezolizumab; clinical pharmacology; pediatric extrapolation; pediatric oncology; physiologically-based pharmacokinetic (PBPK) modeling; quantitative pharmacology; solid tumor.

FIGURE 1

Minimal PBPK model structure and key mechanisms for atezolizumab disposition. The model consists of the blood, lymph node, and lumped tissue compartments. The lumped tissue includes vascular, endosomal, interstitial, and intracellular (not shown) compartments. The 1:1 atezolizumab-FcRn binding at pH 6.0 in the endosomal compartment was considered. The additional clearance (CL_add) is included in the blood compartment. The TMDD is included in the blood compartment, the lymph node compartment, and the interstitial compartment of the lumped tissue. Abbreviations for model parameters are as follows: CL_add,_atezo, additional clearance for atezolizumab; CL_add,IgG,endo, additional clearance for endogenous IgG; CL_TMDD, clearance for atezolizumab via binding to the target PD-L1; CL_cat, the intrinsic catabolic clearance of atezolizumab or endogenous IgG that are not bound to FcRn; FcRn, neonatal Fc receptor; K_D1, equilibrium dissociation constant for atezolizumab-FcRn complex; K_D2, equilibrium dissociation constant for endogenous IgG-FcRn complex; K_rc, endosomal recycling rate; K_up, endosomal uptake rate via fluid phase endocytosis; FR, fraction recycled of FcRn-bound atezolizumab or endogenous IgG; PS_s, permeability surface area product for small pores; PS_l, permeability surface area product for large pores; σ_vs, vascular reflection coefficient through small pores; σ_vl, vascular reflection coefficient through large pores; σ_l, lymphatic reflection coefficient; L, lymph flow rate; Q, blood flow rate.

FIGURE 2

The strategy and workflow of model development, verification, and application for atezolizumab in pediatrics and adult.

FIGURE 3

Simulated mean plasma concentration-time profiles and observed mean concentration data for adult patients with solid tumors and hematologic malignancies after a single IV dose at varying dose levels using the optimized final PBPK model including TMDD. Observed mean data are shown as open circles (Herbst et al., 2014). Simulated mean data are shown as solid lines.

FIGURE 4

Individual observed plasma concentrations (Shemesh et al., 2019) and simulations of multiple IV doses of 15 mg/kg (<18 yo) or 1,200 mg (≥18 yo) atezolizumab Q3W in pediatrics. The panels show data from subjects with different age (A) 16 yo, (B) 15 yo, (C) 13 yo, (D) 12 yo, (E) 11 yo, (F) 10 yo, (G) 8 yo, (H) 7 yo, (I) 5 yo, (J) 4 yo, (K) 3 yo, and (L) 2 yo. Observed data (Shemesh et al., 2019) are shown in red open circles. The green lines represent simulated trials, and the dashed black lines represent the mean data for the entire simulated population (n = 100). The green shaded area represents the 5th to 95th percentiles of the simulations.

FIGURE 5

Individualized simulated mean and observed (Shemesh et al., 2019) plasma concentrations following multiple IV doses of 15 mg/kg (<18 yo) or 1,200 mg (≥18 yo) atezolizumab Q3W in pediatric patients (A) 0–6 yo, (B) 6–12 yo, and (C) 12–18 yo or (D) young adult patients with solid tumors and hematologic malignancies. The solid black lines represent the line of unity and the dashed black lines represent the 2-fold error margin. Each simulation matched the dosing information and demographics with each enrolled subject.

FIGURE 6

Cycle 1 and steady state (cycle 10) simulated atezolizumab (A,B) C_min, (C,D) C_max, and (E,F) AUC_tau for pediatric (2-6 yo, 6–12 yo, and 12–18 yo) and adult (≥18 yo) patients following multiple IV doses of 15 mg/kg (<18 yo) or 1,200 mg (≥18 yo) atezolizumab Q3W. The box represents the median value and interquartile range; error bars represent the 5th and 95th percentiles. Circles represent individual subjects outside of the 5th to 95th percentiles. Shaded area represents the simulated adult acceptable criteria (50%–200% of the adult median value).