Physiologically Based Pharmacokinetic Modeling of Monoclonal Antibodies in Pediatric Populations Using PK-Sim

Abstract

Physiologically based pharmacokinetic (PBPK) models are increasingly used to support pediatric dose selection for small molecule drugs. In contrast, only a few pediatric PBPK models for therapeutic antibodies have been published recently, and the knowledge on the maturation of the processes relevant for antibody pharmacokinetics (PK) is limited compared to small molecules. The aim of this study was, thus, to evaluate predictions from antibody PBPK models for children which were scaled from PBPK models for adults in order to identify respective knowledge gaps. For this, we used the generic PBPK model implemented in PK-Sim without further modifications. Focusing on general clearance and distribution mechanisms, we selected palivizumab and bevacizumab as examples for this evaluation since they show simple, linear PK which is not governed by drug-specific target mediated disposition at usual therapeutic dosages, and their PK has been studied in pediatric populations after intravenous application. The evaluation showed that the PK of palivizumab was overall reasonably well predicted, while the clearance for bevacizumab seems to be underestimated. Without implementing additional ontogeny for antibody PKspecific processes into the PBPK model, bodyweight normalized clearance increases only moderately in young children compared to adults. If growth during aging at the time of the simulation was considered, the apparent clearance is approximately 20% higher compared to simulations for which growth was not considered for newborns due to the long half-life of antibodies. To fully understand the differences and similarities in the PK of antibodies between adults and children, further research is needed. By integrating available information and data, PBPK modeling can contribute to reveal the relevance of involved processes as well as to generate and test hypothesis.

Spreadsheet‐Based Minimal Physiological Models for the Prediction of Clearance of Therapeutic Proteins in Pediatric Patients

“…Taken together, our comprehensive analysis demonstrated that an mPBPK model is a reasonable choice for prediction of clearance of therapeutic proteins in children. Model elaboration with more assumption and inclusion of several unknown parameters (eg, ontogeny of neonatal Fc receptor) did not practically improve the predictive performance of PBPK models 17,23,27–29 …”

“…So far, few whole‐body PBPK or mPBPK models for therapeutic proteins have been evaluated for prediction of PK in children 17,23,27–29 . In 2 studies, Malik and Edginton 17,28 showed that the concentrations of monoclonal antibodies (infliximab, pagibaximab, palivizumab, and MEDI8897) were predicted within a 0.5‐ to 2‐fold error for 67% to 93% of the observations using a whole‐body PBPK model.…”

“…For infliximab, the predictive performance of the whole‐body PBPK and simple allometry models were comparable 17 . In most recent studies, whole‐body 27,29 or mPBPK 23 models focusing on the effects of the neonatal Fc receptor for the prediction of PK parameters in children were evaluated. Although the number of observations were small (n = 4‐26), both whole‐body and mPBPK models predicted clearance or area under the concentration‐time curve of therapeutic proteins within a 0.5‐ to 2‐fold prediction error 23,27,29 .…”

“…In most recent studies, whole‐body 27,29 or mPBPK 23 models focusing on the effects of the neonatal Fc receptor for the prediction of PK parameters in children were evaluated. Although the number of observations were small (n = 4‐26), both whole‐body and mPBPK models predicted clearance or area under the concentration‐time curve of therapeutic proteins within a 0.5‐ to 2‐fold prediction error 23,27,29 . In our analysis, using further simplification of the mPBPK modeling framework and a total of 113 observations, we found that clearance can be predicted within a 0.5‐ to 2‐fold prediction error for >90% of the observations.…”

Mechanistic Modelling Identifies and Addresses the Risks of Empiric Concentration-Guided Sorafenib Dosing

“…Many early studies focussed on a potential role for TDM-guided KI dosing, however, sufficient evidence has yet to be generated to support widespread implementation for any KI. This has led to the exploration of novel approaches to facilitate precision KI dosing, which have included model informed precision dosing based on integrated simulation/prediction platforms such as PK-Sim ® , GastroPlus TM , Phoenix TM , and Simcyp ® [ 26 , 36 , 37 , 38 ].…”