A Model-Based Approach to Quantify the Time-Course of Anti-Drug Antibodies for Therapeutic Proteins

Physiologically-based pharmacokinetic modeling to predict the exposure and provide dosage regimens of adalimumab in patients with juvenile idiopathic arthritis

BACKGROUND

Adalimumab has been approved for treating juvenile idiopathic arthritis (JIA). This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model for adalimumab in JIA patients to optimize personalized treatment.

METHODS

A comprehensive literature search identified 13 clinical studies as the dataset for constructing and validating a PBPK model of adalimumab. Initially, a PBPK model for adalimumab in adults was constructed using PK-Sim and Mobi software. Subsequently, virtual pediatric populations were created by incorporating age-dependent parameters from the PK-Sim database, extending the model to JIA patients. Finally, based on the developed PBPK model for adalimumab in JIA patients, dosing regimens were evaluated for different age groups.

RESULTS

This study successfully developed and validated a PBPK model for adalimumab in both adult and pediatric populations. The model for adults accurately predicted 92.90% of the concentrations within 0.5-2 times the observed values, while the pediatric model predicted 90.62% of the concentrations within 0.5-2-fold range. For pediatric patients with JIA, age- and weight-based dosing is recommended to achieve trough concentrations comparable to those in adults.

CONCLUSION

A PBPK model for adalimumab in pediatric patients with JIA was developed, providing a basis for personalized dosing regimens in this population.

Model-Informed Immunogenicity Assessment of Nivolumab as Monotherapy and in Combination with Ipilimumab

Immunogenicity to biotherapeutics can lead to antidrug antibodies (ADAs) that have potential to alter pharmacokinetics (PK), efficacy, and safety. Here we provide an extensive model-informed immunogenicity assessments of nivolumab monotherapy and in combination with ipilimumab across multiple clinical trials. ADA was evaluated as both a binary and semiquantitative covariate, incorporating ADA titers to account for intensity over time. Data from 28 clinical trials, including 7,820 subjects with 2,770 ADA titer measurements, were analyzed using population pharmacokinetic (popPK) modeling. Nivolumab ADA incidence rate was higher for combination therapy (~ 32%) compared to monotherapy (~ 16%). ADA increased nivolumab clearance (CL) by 20-80% depending on titer. Nivolumab ADA impact on efficacy and safety was evaluated in melanoma and non-small cell lung cancer (NSCLC) patients. Despite the occurrence of nivolumab ADA being associated with lower nivolumab exposures, objective response rates (ORR) were similar in ADA-positive and negative patients, and ADA titer was not a significant predictor of response. An overall survival (OS) landmark analysis at 3 months suggested similar OS for NSCLC but lower OS for melanoma for ADA-positive vs negative patients mainly due to the imbalanced patient baseline characteristics. Propensity score matching and multivariable Cox Proportional-Hazards analysis indicated no ADA impact on OS. Additionally, there were no associations between ADA and acute hypersensitivities or immune mediated safety events. This model-based approach underscores the importance of accounting for ADA dynamics in clinical development and supports no significant association between ADA presence and clinical efficacy or safety, even with higher ADA incidence in combination therapy.

Impact of Switching on Pharmacokinetics of Therapeutic Biologics and Interchangeability Assessment-A Simulation Study

The risk in terms of safety or diminished efficacy of switching between an originator biological product and a proposed interchangeable product is an important consideration for interchangeability evaluation in the regulatory framework. This simulation study evaluated the impact of several switching study design scenarios on the pharmacokinetic (PK) assessment between a virtual originator biological product and a virtual proposed interchangeable product. Our results show that (1) at least 3 switches are needed to optimize the detection of potential PK differences, (2) the initial incidence of antidrug antibodies after treatment with the reference product in the lead-in period is a significant covariate affecting the PK results, and (3) the area under the concentration-time curve is more sensitive than peak concentration in assessing the impact of switching on PK similarity. Our simulation work illustrates that a range of factors should be carefully considered when designing a switching study for the assessment of interchangeability between 2 biological products.

Physiologically-Based Pharmacokinetic Modeling vs. Allometric Scaling for the Prediction of Infliximab Pharmacokinetics in Pediatric Patients

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.