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

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 Cmin, Cmax, and AUCtau 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.

Considerations and Caveats when Applying Global Sensitivity Analysis Methods to Physiologically Based Pharmacokinetic Models.

Three global sensitivity analysis (GSA) methods (Morris, Sobol and extended Sobol) are applied to a minimal physiologically based PK (mPBPK) model using three model drugs given orally, namely quinidine, alprazolam, and midazolam. We investigated how correlations among input parameters affect the determination of the key parameters influencing pharmacokinetic (PK) properties of general interest, i.e., the maximal plasma concentration (Cmax) time at which Cmax is reached (Tmax), and area under plasma concentration (AUC). The influential parameters determined by the Morris and Sobol methods (suitable for independent model parameters) were compared to those determined by the extended Sobol method (which considers model parameter correlations). For the three drugs investigated, the Morris method was as informative as the Sobol method. The extended Sobol method identified different sets of influential parameters to Morris and Sobol. These methods overestimated the influence of volume of distribution at steady state (Vss) on AUC24h for quinidine and alprazolam. They also underestimated the effect of volume of liver (Vliver) for all three drugs, the impact of enzyme intrinsic clearance of CYP2C9 and CYP2E1 for quinidine, and that of UGT1A4 abundance for midazolam. Our investigation showed that the interpretation of GSA results is not straightforward. Dismissing existing model parameter correlations, GSA methods such as Morris and Sobol can lead to biased determination of the key parameters for the selected outputs of interest. Decisions regarding parameters' influence (or otherwise) should be made in light of available knowledge including the model assumptions, GSA method limitations, and inter-correlations between model parameters, particularly in complex models. Graphical abstract.

A Bottom-Up Whole-Body Physiologically Based Pharmacokinetic Model to Mechanistically Predict Tissue Distribution and the Rate of Subcutaneous Absorption of Therapeutic Proteins.

The ability to predict subcutaneous (SC) absorption rate and tissue distribution of therapeutic proteins (TPs) using a bottom-up approach is highly desirable early in the drug development process prior to clinical data being available. A whole-body physiologically based pharmacokinetic (PBPK) model, requiring only a few drug parameters, to predict plasma and interstitial fluid concentrations of TPs in humans after intravenous and subcutaneous dosing has been developed. Movement of TPs between vascular and interstitial spaces was described by considering both convection and diffusion processes using a 2-pore framework. The model was optimised using a variety of literature sources, such as tissue lymph/plasma concentration ratios in humans and animals, information on the percentage of dose absorbed following SC dosing via lymph in animals and data showing loss of radiolabelled IgG from the SC dosing site in humans. The resultant model was used to predict t max and plasma concentration profiles for 12 TPs (molecular weight 8-150 kDa) following SC dosing. The predicted plasma concentration profiles were generally comparable to observed data. t max was predicted within 3-fold of reported values, with one third of the predictions within 0.8-1.25-fold. There was no systematic bias in simulated C max values, although a general trend for underprediction of t max was observed. No clear trend between prediction accuracy of t max and TP isoelectric point or molecular size was apparent. The mechanistic whole-body PBPK model described here can be applied to predict absorption rate of TPs into blood and movement into target tissues following SC dosing.

Simulation of monoclonal antibody pharmacokinetics in humans using a minimal physiologically based model.

Compared to small chemical molecules, monoclonal antibodies and Fc-containing derivatives (mAbs) have unique pharmacokinetic behaviour characterised by relatively poor cellular permeability, minimal renal filtration, binding to FcRn, target-mediated drug disposition, and disposition via lymph. A minimal physiologically based pharmacokinetic (PBPK) model to describe the pharmacokinetics of mAbs in humans was developed. Within the model, the body is divided into three physiological compartments; plasma, a single tissue compartment and lymph. The tissue compartment is further sub-divided into vascular, endothelial and interstitial spaces. The model simultaneously describes the levels of endogenous IgG and exogenous mAbs in each compartment and sub-compartment and, in particular, considers the competition of these two species for FcRn binding in the endothelial space. A Monte-Carlo sampling approach is used to simulate the concentrations of endogenous IgG and mAb in a human population. Existing targeted-mediated drug disposition (TMDD) models are coupled with the minimal PBPK model to provide a general platform for simulating the pharmacokinetics of therapeutic antibodies using primarily pre-clinical data inputs. The feasibility of utilising pre-clinical data to parameterise the model and to simulate the pharmacokinetics of adalimumab and an anti-ALK1 antibody (PF-03446962) in a population of individuals was investigated and results were compared to published clinical data.

Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model.

Although advantages of physiologically based pharmacokinetic models (PBPK) are now well established, PBPK models that are linked to pharmacodynamic (PD) models to predict pharmacokinetics (PK), PD, and efficacy of monoclonal antibodies (mAbs) in humans are uncommon. The aim of this study was to develop a PD model that could be linked to a physiologically based mechanistic FcRn model to predict PK, PD, and efficacy of efalizumab. The mechanistic FcRn model for mAbs with target-mediated drug disposition within the Simcyp population-based simulator was used to simulate the pharmacokinetic profiles for three different single doses and two multiple doses of efalizumab administered to virtual Caucasian healthy volunteers. The elimination of efalizumab was modeled with both a target-mediated component (specific) and catabolism in the endosome (non-specific). This model accounted for the binding between neonatal Fc receptor (FcRn) and efalizumab (protective against elimination) and for changes in CD11a target concentration. An integrated response model was then developed to predict the changes in mean Psoriasis Area and Severity Index (PASI) scores that were measured in a clinical study as an efficacy marker for efalizumab treatment. PASI scores were approximated as continuous and following a first-order asymptotic progression model. The reported steady state asymptote (Y ss) and baseline score [Y (0)] was applied and parameter estimation was used to determine the half-life of progression (T p) of psoriasis. Results suggested that simulations using this model were able to recover the changes in PASI scores (indicating efficacy) observed during clinical studies. Simulations of both single dose and multiple doses of efalizumab concentration-time profiles as well as suppression of CD11a concentrations recovered clinical data reasonably well. It can be concluded that the developed PBPK FcRn model linked to a PD model adequately predicted PK, PD, and efficacy of efalizumab.

Report on childhood obesity in China (8): effects and sustainability of physical activity intervention on body composition of Chinese youth.

OBJECTIVES: To determine whether a large-scale physical activity intervention could affect body composition in primary school students in Beijing, China. METHODS: The study design was one-year cluster randomized controlled trial of physical activity intervention (20 min of daily exercise in the classroom) with an additional year of follow-up among 4 700 students aged 8-11 years at baseline. RESULTS: After the one-year intervention, BMI increased by 0.56 kg/m(2) (SD 1.15) in the intervention group and by 0.72 kg/m(2) (SD 1.20) in the control group, with a mean difference of -0.15 kg/m(2) (95% CI: -0.28 to -0.02). BMI z score decreased by -0.05 (SD 0.44) in the intervention group, but increased by 0.01 (SD 0.46) in the control group, with a mean difference of -0.07 (-0.13 to -0.01). After another year of follow up, compared to the control group, children in the intervention group had significantly lower BMI (-0.13, -0.25 to -0.01), BMI z score (-0.05, -0.10 to -0.01), fat mass (-0.27 kg, -0.53 to -0.02) and percent body fat (-0.53, -1.00 to -0.05). The intervention had a more pronounced effect on weight, height, BMI, BMI z score, and body composition among obese children than among normal weight or overweight children. Compared to the control group, the intervention group had a significantly higher percentage of children who maintained or reduced their BMI z score at year 1 (P=0.008) and year 2 (P=0.04). CONCLUSIONS: These findings suggest that 20 min of daily moderate to vigorous physical activity during the school year is a feasible and effective way to prevent excessive gain of body weight, BMI, and body fatness in primary school students.

Integrating biosystem models using waveform relaxation.

Modelling in systems biology often involves the integration of component models into larger composite models. How to do this systematically and efficiently is a significant challenge: coupling of components can be unidirectional or bidirectional, and of variable strengths. We adapt the waveform relaxation (WR) method for parallel computation of ODEs as a general methodology for computing systems of linked submodels. Four test cases are presented: (i) a cascade of unidirectionally and bidirectionally coupled harmonic oscillators, (ii) deterministic and stochastic simulations of calcium oscillations, (iii) single cell calcium oscillations showing complex behaviour such as periodic and chaotic bursting, and (iv) a multicellular calcium model for a cell plate of hepatocytes. We conclude that WR provides a flexible means to deal with multitime-scale computation and model heterogeneity. Global solutions over time can be captured independently of the solution techniques for the individual components, which may be distributed in different computing environments.

[Study on the relation between anthropometric parameters and lipids profiles].

OBJECTIVE: To study the relations between anthropometric parameters [body mass index (BMI), percent of body fat, waist circumference] and blood lipids of urban children in Beijing and to compare the ability of prediction effect of waist circumference, percent body fat and BMI on lipid profiles. METHODS: 852 children aged 9-10 were recruited with multi-stage sampling. Serum lipids of children were measured using automatic biochemical instrument. Fisher's exact test, trend test and median regression were used to analyze the data from 847 subjects with valid information. RESULTS: (1)With the rise of the BMI, percent body fat and waist circumference, total triglycerides (TG), total cholesterol (TC) and low density lipoprotein choleasterol (LDL-C) showed increasing trends while high density lipoprotein choleasterol (HDL-C) had a decreasing trend(P < 0.01). (2)TG was mainly influenced by waist circumference (t = 6.86), sex (t = 3.96) and percent of body fat (t = 1.85); TC was influenced by percent of body fat (t = 5.31); LDL-C was influenced by waist circumference (t = 4.65), height (t = -2.79) and percent age of body fat (t = 2.77); HDL-C was influenced by waist circumference (t = -12.24), sex (1= -5.83). CONCLUSION: With the aggravation of children's fatness (BMI, WC and PBF), serum lipids would increase and WC seemed to be the best predictor for lipids among BMI, WC and PBF.