Dose design for pediatric trials with monoclonal antibodies (mAbs) is often extrapolated from the adult dose according to weight, age, or body surface area. While these methods account for the size differences between adults and children, they do not account for the maturation of processes that may play a key role in the pharmacokinetics and/or pharmacodynamics of mAbs. With the same weight-based dose, infants and young children typically receive lower plasma exposures when compared to adults. Areas covered: The mechanistic features of mAb distribution, elimination, and absorption are explored in detail and literature-based hypotheses are generated to describe their age-dependence. This knowledge can be incorporated into a physiologically based pharmacokinetic (PBPK) modeling approach to pediatric dose determination. Expert opinion: As data from pediatric clinical trials become increasingly available, we have the opportunity to reflect on the physiologic drivers of pharmacokinetics, safety, and efficacy in children with mathematical models. A modeling approach that accounts for the age-related features of mAb disposition can be used to derive first-in-pediatric doses, design optimal sampling schemes for children in clinical trials and even explore new pharmacokinetic end-points as predictors of safety and efficacy in children.

The comparative performances of physiologically‐based pharmacokinetic (PBPK) modeling and allometric scaling for predicting the pharmacokinetics (PKs) of large molecules in pediatrics are unknown. Therefore, both methods were evaluated for accuracy in translating knowledge of infliximab PKs from adults to children. PBPK modeling was performed using the base model for large molecules in PK‐Sim version 7.4 with modifications in Mobi. Eight population PK models from literature were reconstructed and scaled by allometry to pediatrics. Evaluation data included seven pediatric studies (~4–18 years). Both methods performed comparably with 66.7% and 68.6% of model‐predicted concentrations falling within twofold of the observed concentrations for PBPK modeling and allometry, respectively. Considerable variability was noted among the allometric models. Therefore, pediatric clinical trial planning would benefit from using approaches that require predictions depending on the specific question i.e., PBPK modeling and allometry.

Gold nanoparticles (AuNPs) are a focus of growing medical research applications due to their unique chemical, electrical and optical properties. Because of uncertain toxicity, “green” synthesis methods are emerging, using plant extracts to improve biological and environmental compatibility. Here we explore the biodistribution of green AuNPs in mice and prepare a physiologically-based pharmacokinetic (PBPK) model to guide interspecies extrapolation. Monodisperse AuNPs were synthesized and capped with epigallocatechin gallate (EGCG) and curcumin. 64 CD-1 mice received the AuNPs by intraperitoneal injection. To assess biodistribution, groups of six mice were sacrificed at 1, 7, 14, 28 and 56 days, and their organs were analyzed for gold content using inductively coupled plasma mass spectrometry (ICP-MS). A physiologically-based pharmacokinetic (PBPK) model was developed to describe the biodistribution data in mice. To assess the potential for interspecies extrapolation, organism-specific parameters in the model were adapted to represent rats, and the rat PBPK model was subsequently evaluated with PK data for citrate-capped AuNPs from literature. The liver and spleen displayed strong uptake, and the PBPK model suggested that extravasation and phagocytosis were key drivers. Organ predictions following interspecies extrapolation were successful for rats receiving citrate-capped AuNPs. This work lays the foundation for the pre-clinical extrapolation of the pharmacokinetics of AuNPs from mice to larger species.

An understanding of pediatric pharmacokinetics (PK) is essential for first‐in‐pediatric dose selection and clinical trial design. At present, there is no reliable way to scale the PK of monoclonal antibodies and immunoglobulin G drug products from adults to young children or to premature infants—a vulnerable population with a rapidly growing drug development pipeline. In this work, pediatric physiologically based PK models are constructed in PK‐Sim and Mobi to explore the PK of pagibaximab, palivizumab, MEDI8897, and intravenous immunoglobulin in preterm infants. In addition to considering ontogeny in pediatric organ volumes, organ composition, blood flow rates, and hematocrit, advanced ontogeny is applied for 3 key parameters: capillary surface area, hematopoietic cell concentration, and lymph flow rate. The role and importance of each parameter for determining pediatric clearance (CL) and volume of distribution at steady state (VSS) are quantitatively assessed with a local sensitivity analysis. In addition, the uncertainty around parameters with limited information in pediatrics is addressed (eg, free neonatal Fc receptor concentration). The full ontogeny parameterization yields pediatric PK predictions that are within 1.5‐fold prediction error >90% of the time for preterm infants, with an absolute average fold error of 1.05. This result suggests that many of the key factors related to ontogeny are appropriately addressed. Overall, this study makes a first step toward developing a platform pediatric physiologically based PK model for monoclonal antibodies and immunoglobulin G drug products by solidifying existing parameterizations, integrating new concepts, and drawing attention to unmet needs for physiologic knowledge in children.

Despite the many benefits of breast milk, mothers taking medication are often uncertain about the risks of drug exposure to their infants and decide not to breastfeed. Physiologically based pharmacokinetic models can contribute to drug‐in‐milk safety assessments by predicting the infant exposure and subsequently, risk for toxic effects that would result from continuous breastfeeding. This review aimed to quantify breast milk intake feeding parameters in term and preterm infants using literature data for input into paediatric physiologically based pharmacokinetic models designed for drug‐in‐milk risk assessment. Ovid MEDLINE and Embase were searched up to July 2, 2019. Key study reference lists and grey literature were reviewed. Title, abstract and full text were screened in nonduplicate. Daily weight‐normalized human milk intake (WHMI) and feeding frequency by age were extracted. The review process retrieved 52 studies. A nonlinear regression equation was constructed to describe the WHMI of exclusively breastfed term infants from birth to 1 year of age. In all cases, preterm infants fed with similar feeding parameters to term infants on a weight‐normalized basis. Maximum WHMI was 152.6 ml/kg/day at 19.7 days, and weighted mean feeding frequency was 7.7 feeds/day. Existing methods for approximating breast milk intake were refined by using a comprehensive set of literature data to describe WHMI and feeding frequency. Milk feeding parameters were quantified for preterm infants, a vulnerable population at risk for high drug exposure and toxic effects. A high‐risk period of exposure at 2–4 weeks of age was identified and can inform future drug‐in‐milk risk assessments.