Toward systems-informed models for biologics disposition: covariates of the abundance of the neonatal Fc Receptor (FcRn) in human tissues and implications for pharmacokinetic modelling

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook

Over the past 20 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. A symposium at the 25th North American International Society for the Study of Xenobiotics meeting, in Boston, in September 2023, was held to explore current and emerging applications of quantitative proteomics in translational pharmacology and strategies for improved integration into model-informed drug development based on practical experience of each of the presenters. A summary of the talks and discussions is presented in this perspective alongside future outlook that was outlined for future meetings. SIGNIFICANCE STATEMENT: This perspective explores current and emerging applications of quantitative proteomics in translational pharmacology and precision medicine and outlines the outlook for improved integration into model-informed drug development.

Dealing With Variable Drug Exposure Due to Variable Hepatic Metabolism: A Proof-of-Concept Application of Liquid Biopsy in Renal Impairment

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics (PK), affecting drug exposure, and in pharmacodynamics (PD), affecting response achieved at the same drug concentration at the site of action. Although liquid biopsy for assessing different levels of molecular drug targets has yet to be established, individual characterization of drug elimination pathways using liquid biopsy has recently been demonstrated. The feasibility of applying this approach in conjunction with modeling tools to guide individual dosing remains unexplored. In this study, we aimed to individualize physiologically-based pharmacokinetic (PBPK) models based on liquid biopsy measurements in plasma from 25 donors with different grades of renal function who were previously administered oral midazolam as part of a microdose cocktail. Virtual twin models were constructed based on demographics, renal function, and hepatic expression of relevant pharmacokinetic pathways projected from liquid biopsy output. Simulated exposure (AUC) to midazolam was in agreement with observed data (AFE = 1.38, AAFE = 1.78). Simulated AUC variability with three dosing approaches indicated higher variability with uniform dosing (14-fold) and stratified dosing (13-fold) compared with individualized dosing informed by liquid biopsy (fivefold). Further, exosome screening revealed mRNA expression of 532 targets relevant to drug metabolism and disposition (169 enzymes and 361 transporters). Data related to these targets can be used to further individualize PBPK models for pathways relevant to PK of other drugs. This study provides additional verification of liquid biopsy-informed PBPK modeling approaches, necessary to advance strategies that seek to achieve precise dosing from the start of treatment.

Population Pharmacokinetics of Nirsevimab in Preterm and Term Infants

Nirsevimab, a monoclonal antibody with an extended half-life, is approved for the prevention of respiratory syncytial virus (RSV) disease in all infants in Canada, the EU, Great Britain, and the USA. A population pharmacokinetics (PK) model was built to describe the PK of nirsevimab in preterm and term infants, and to evaluate the influence of covariates, including body weight and age, in infants. Nirsevimab PK was characterized by a 2-compartment model with first-order clearance (CL) and first-order absorption following intramuscular (IM) administration. The typical CL in a 5 kg infant was 3.4 mL/day. Body weight and postmenstrual age were the primary covariates on CL, with minor effects for race, second RSV season, and antidrug antibody status (deemed not clinically relevant). Congenital heart disease (CHD) and chronic lung disease (CLD) did not significantly impact nirsevimab PK. The final population PK model, based on 8987 PK observations from 2683 participants across 5 clinical trials, successfully predicted PK in an additional cohort of 967 healthy infants. Weight-banded dosing (50 mg in infants <5 kg; 100 mg in infants ≥5 kg) was predicted to be appropriate for infants ≥1 kg in their first RSV season. Together, these data support weight-banded dosing of nirsevimab in all infants in their first RSV season, including in healthy infants, infants with CHD or CLD, and in infants born prematurely.

A Mechanistic Physiologically-Based Pharmacokinetic Platform Model to Guide Adult and Pediatric Intravenous and Subcutaneous Dosing for Bispecific T Cell Engagers

Bispecific T cell engagers (Bi-TCEs) have revolutionized the treatment of oncology indications across both liquid and solid tumors. Bi-TCEs are rapidly evolving from conventional intravenous (i.v.) to more convenient subcutaneous (s.c.) administrations and extending beyond adults to also benefit pediatric patients. Leveraging clinical development experience across three generations of Bi-TCE molecules across both liquid and solid tumor indications from i.v./s.c. dosing in adults and pediatric subjects, we developed a mechanistic-physiologically-based pharmacokinetic (PBPK) platform model for Bi-TCEs. The model utilizes a full PBPK model framework and was successfully validated for PK predictions following i.v. and s.c. dosing across both liquid and solid tumor space in adults for eight Bi-TCEs. After refinement to incorporate physiological ontogeny, the model was successfully validated to predict pediatric PKs in 1 month - < 2 years, 2-11 years, and 12-17 years old subjects following i.v. dosing. Following s.c. dosing in pediatric subjects, the model predicted similar bioavailability, however, a shorter time to maximum concentration (Tmax ) for the three age groups compared with adults. The model was also applied to guide the dosing strategy for first generation of Bi-TCEs for organ impairment, specifically renal impairment, and was able to accurately predict the impact of renal impairment on PK for these relatively small-size Bi-TCEs. This work highlights a novel mechanistic platform model for accurately predicting the PK in adult and pediatric patients across liquid and solid tumor indications from i.v./s.c. dosing and can be used to guide optimal dose and dosing regimen selection and accelerating the clinical development for Bi-TCEs.

Novel Approaches to Characterize Individual Drug Metabolism and Advance Precision Medicine

Interindividual variability in drug metabolism can significantly affect drug concentrations in the body and subsequent drug response. Understanding an individual's drug metabolism capacity is important for predicting drug exposure and developing precision medicine strategies. The goal of precision medicine is to individualize drug treatment for patients to maximize efficacy and minimize drug toxicity. While advances in pharmacogenomics have improved our understanding of how genetic variations in drug-metabolizing enzymes (DMEs) affect drug response, nongenetic factors are also known to influence drug metabolism phenotypes. This minireview discusses approaches beyond pharmacogenetic testing to phenotype DMEs-particularly the cytochrome P450 enzymes-in clinical settings. Several phenotyping approaches have been proposed: traditional approaches include phenotyping with exogenous probe substrates and the use of endogenous biomarkers; newer approaches include evaluating circulating noncoding RNAs and liquid biopsy-derived markers relevant to DME expression and function. The goals of this minireview are to 1) provide a high-level overview of traditional and novel approaches to phenotype individual drug metabolism capacity, 2) describe how these approaches are being applied or can be applied to pharmacokinetic studies, and 3) discuss perspectives on future opportunities to advance precision medicine in diverse populations. SIGNIFICANCE STATEMENT: This minireview provides an overview of recent advances in approaches to characterize individual drug metabolism phenotypes in clinical settings. It highlights the integration of existing pharmacokinetic biomarkers with novel approaches; also discussed are current challenges and existing knowledge gaps. The article concludes with perspectives on the future deployment of a liquid biopsy-informed physiologically based pharmacokinetic strategy for patient characterization and precision dosing.

Application of Modelling and Simulation Approaches to Predict Pharmacokinetics of Therapeutic Monoclonal Antibodies in Pediatric Population

Ethical regulations and limited paediatric participants are key challenges that contribute to a median delay of 6 years in paediatric mAb approval. To overcome these barriers, modelling and simulation methodologies have been adopted to design optimized paediatric clinical studies and reduce patient burden. The classical modelling approach in paediatric pharmacokinetic studies for regulatory submissions is to apply body weight-based or body surface area-based allometric scaling to adult PK parameters derived from a popPK model to inform the paediatric dosing regimen. However, this approach is limited in its ability to account for the rapidly changing physiology in paediatrics, especially in younger infants. To overcome this limitation, PBPK modelling, which accounts for the ontogeny of key physiological processes in paediatrics, is emerging as an alternative modelling strategy. While only a few mAb PBPK models have been published, PBPK modelling shows great promise demonstrating a similar prediction accuracy to popPK modelling in an Infliximab paediatric case study. To facilitate future PBPK studies, this review consolidated comprehensive data on the ontogeny of key physiological processes in paediatric mAb disposition. To conclude, this review discussed different use-cases for pop-PK and PBPK modelling and how they can complement each other to increase confidence in pharmacokinetic predictions.