Comparison of Various Approaches to Translate Non-Linear Pharmacokinetics of Monoclonal Antibodies from Cynomolgus Monkey to Human

Translate Pharmacokinetics of PD-1/PD-L1 Monoclonal Antibodies from Cynomolgus Monkey to Human: Comparison of Different Approaches

Antibodies blocking programmed death-1 (PD-1) and its natural ligand programmed death-ligand 1 (PD-L1) have been proved to be promising strategies in recent years. Hundreds of PD-1/PD-L1 antibodies are under development worldwide. Prediction of human pharmacokinetics (PK) in the preclinical stage is critical for designing dosing regimens in first-in-human studies. This study aims to predict the PK of PD-1/PD-L1 antibodies in human by scaling of monkey data. A systematic literature search of published articles on the PK of PD-1/PD-L1 antibodies in cynomolgus monkey and in human was conducted. Allometric scaling (AS), the species time-invariant (STIV) method, as well as physiologically based pharmacokinetic (PBPK) modeling were investigated. Six antibodies (avelumab, atezolizumab, nivolumab, pembrolizumab, cemiplimab, and zimberelimab) were included for investigation. The exponents used in this study were 0.85 and 1 for clearance (CL) and distribution volume (V), respectively, both for AS and STIV methods. The generic PBPK model for macromolecules in PK-Sim was used without further modifications. The dissociation constant of the antibody for binding to FcRn (KD) in endosome space for human was assumed to be two-fold of that for monkey. Predicted human CLs for the majority of drugs were within the observed range, while Vs were not well predicted using the AS method. The STIV method and the generic PBPK model can be employed to translate concentration-time curves of PD-1/PD-L1 antibodies from cynomolgus monkey to human with comparable efficacy. The results of this study provide reference for the early development of PD-1/PD-L1 antibodies.

Application of Allometric Scaling to Nanochelator Pharmacokinetics

Deferoxamine (DFO) is an effective FDA-approved iron chelator; however, its use is considerably limited by off-target toxicities and an extremely cumbersome dose regimen involving daily infusions. The recent development of a deferoxamine-based nanochelator (DFO-NP) with selective renal excretion has shown promise in ameliorating iron overload and associated physiological complications in rodent models with a substantially improved safety profile. While the dose- and administration route-dependent pharmacokinetics (PK) of DFO-NPs have been recently characterized, the optimized PK model was not validated, and the prior studies did not directly address the clinical translatability of DFO-NPs into humans. In the present work, these gaps were addressed by applying allometric scaling of DFO-NP PK in rats to predict those in mice and humans. First, this approach predicted serum concentration-time profiles of DFO-NPs, which were similar to those experimentally measured in mice, validating the nonlinear disposition and absorption models for DFO-NPs across the species. Subsequently, we explored the utility of allometric scaling by predicting the PK profile of DFO-NPs in humans under clinically relevant dosing schemes. These in silico efforts demonstrated that the novel nanochelator is expected to improve the PK of DFO when compared to standard infusion regimens of native DFO. Moreover, reasonable formulation strategies were identified and discussed for both early clinical development and more sophisticated formulation development.

Mathematical modeling of SARS-CoV-2 viral dynamics and treatment with monoclonal antibodies

The novel coronavirus (SARS-CoV-2) affects primarily the respiratory tract, and if left unchecked can cause a spectrum of pathological manifestations such as pneumonia, acute respiratory distress syndrome, myocardial injury, thromboembolism, and acute kidney injury. Medication strategies have involved minimizing the spread of the virus through antiviral medications (monoclonal antibodies or nucleotide reverse transcriptase inhibitors). Here, we develop a mathematical model that simulates viral dynamics in an untreated individual, and the evaluate the impact that a monoclonal antibody can have on slowing viral replication. Drug pharmacokinetics (PK) was informed by a typical two-compartment PK model with parameters typical of a monoclonal antibody, with a third compartment for the lung included as the drug site of action. The viral dynamics were captured using a simplified model describing uninfected target cells, infected target cells, and viral load in the body. The mechanism of action of the simulated antiviral is based on binding to the virus, thereby preventing it from infecting healthy cells. The model is used to project dosages needed to prevent severe disease under a variety of simulated conditions and subject to realistic constraints. The proposed model can capture a variety of scenarios of longitudinal viral dynamics and assess the impact of antiviral therapy on disease severity and duration. The described approach can be easily adapted to rapidly assess the dosages needed to affect duration and outcome of other viral infections and can serve as part of a fast and efficient scientific and modeling response strategy in the future as needed.

Review of the Existing Translational Pharmacokinetics Modeling Approaches Specific to Monoclonal Antibodies (mAbs) to Support the First-In-Human (FIH) Dose Selection

The interest in therapeutic monoclonal antibodies (mAbs) has continuously growing in several diseases. However, their pharmacokinetics (PK) is complex due to their target-mediated drug disposition (TMDD) profiles which can induce a non-linear PK. This point is particularly challenging during the pre-clinical and translational development of a new mAb. This article reviews and describes the existing PK modeling approaches used to translate the mAbs PK from animal to human for intravenous (IV) and subcutaneous (SC) administration routes. Several approaches are presented, from the most empirical models to full physiologically based pharmacokinetic (PBPK) models, with a focus on the population PK methods (compartmental and minimal PBPK models). They include the translational approaches for the linear part of the PK and the TMDD mechanism of mAbs. The objective of this article is to provide an up-to-date overview and future perspectives of the translational PK approaches for mAbs during a model-informed drug development (MIDD), since the field of PK modeling has gained recently significant interest for guiding mAbs drug development.

Application of physiologically-based pharmacokinetic models for therapeutic proteins and other novel modalities

The past two decades have seen diversification of drug development pipelines and approvals from traditional small molecule therapies to alternative modalities including monoclonal antibodies, engineered proteins, antibody drug conjugates (ADCs), oligonucleotides and gene therapies. At the same time, physiologically-based pharmacokinetic (PBPK) models for small molecules have seen increased industry and regulatory acceptance.This review focusses on the current status of the application of PBPK models to these newer modalities and give a perspective on the successes, challenges and future directions of this field.There is greatest experience in the development of PBPK models for therapeutic proteins, and PBPK models for ADCs benefit from prior experience for both therapeutic proteins and small molecules. For other modalities, the application of PBPK models is in its infancy.Challenges are discussed and a common theme is lack of availability of physiological and experimental data to characterise systems and drug parameters to enable a priori prediction of pharmacokinetics. Furthermore, sufficient clinical data are required to build confidence in developed models.The PBPK modelling approach provides a quantitative framework for integrating knowledge and data from multiple sources and can be built on as more data becomes available.

Preclinical Characterization of ASP2713, a Novel Igβ and FcγRIIB Cross-Linking Antibody, for Prediction of Human Pharmacokinetics and Clinically Effective Dose

Previously, we reported the fundamental pharmacological characteristics of a novel Igβ and Fc gamma receptor IIB cross-linking antibody, ASP2713, as a new treatment option for systemic lupus erythematosus. The aims of the present study were to investigate ASP2713's characteristics with regard to pharmacological effect, pharmacokinetics (PK), and receptor occupancy, and to predict its human PK and clinically effective dose. The relationship between the concentration and receptor occupancy of ASP2713 for Igβ of B cell receptors was examined using whole blood B cells. Calculated EC₅₀ values in cynomolgus monkeys and healthy volunteers were 0.35 and 0.058 μg/mL, respectively. Dose-dependent inhibition of anti-tetanus toxoid (TTx) antibody production, PK, and receptor occupancy of ASP2713 in TTx-sensitized cynomolgus monkeys suggested a minimally effective dose of 1 mg/kg by single intravenous (IV) administration. Scaling-up of monkey PK parameters to humans by allometric scaling predicted a clinically effective dose of 0.4 mg/kg IV administration at 4-week intervals to maintain a trough concentration in humans which achieved the same receptor occupancy expected at the effective dose in monkeys. This study aids in understanding the characteristics of ASP2713 and can be used as a basis for clinical dose setting.

Recent Advances in Translational Pharmacokinetics and Pharmacodynamics Prediction of Therapeutic Antibodies Using Modeling and Simulation

Therapeutic monoclonal antibodies (mAbs) have been a promising therapeutic approach for several diseases and a wide variety of mAbs are being evaluated in clinical trials. To accelerate clinical development and improve the probability of success, pharmacokinetics and pharmacodynamics (PKPD) in humans must be predicted before clinical trials can begin. Traditionally, empirical-approach-based PKPD prediction has been applied for a long time. Recently, modeling and simulation (M&S) methods have also become valuable for quantitatively predicting PKPD in humans. Although several models (e.g., the compartment model, Michaelis–Menten model, target-mediated drug disposition model, and physiologically based pharmacokinetic model) have been established and used to predict the PKPD of mAbs in humans, more complex mechanistic models, such as the quantitative systemics pharmacology model, have been recently developed. This review summarizes the recent advances and future direction of M&S-based approaches to the quantitative prediction of human PKPD for mAbs.