Linear pharmacokinetic parameters for monoclonal antibodies are similar within a species and across different pharmacological targets: A comparison between human, cynomolgus monkey and hFcRn Tg32 transgenic mouse using a population-modeling approach

Abstract

The linear pharmacokinetics (PK) of therapeutic monoclonal antibodies (mAbs) can be considered a class property with values that are similar to endogenous IgG. Knowledge of these parameters across species could be used to avoid unnecessary in vivo PK studies and to enable early PK predictions and pharmacokinetic/pharmacodynamic (PK/PD) simulations. In this work, population-pharmacokinetic (popPK) modeling was used to determine a single set of 'typical' popPK parameters describing the linear PK of mAbs in human, cynomolgus monkey and transgenic mice expressing the human neonatal Fc receptor (hFcRn Tg32), using a rich dataset of 27 mAbs. Non-linear PK was excluded from the datasets and a 2-compartment model was applied to describe mAb disposition. Typical human popPK estimates compared well with data from comparator mAbs with linear PK in the clinic. Outliers with higher than typical clearance were found to have non-specific interactions in an affinity-capture self-interaction nanoparticle spectroscopy assay, offering a potential tool to screen out these mAbs at an early stage. Translational strategies were investigated for prediction of human linear PK of mAbs, including use of typical human popPK parameters and allometric exponents from cynomolgus monkey and Tg32 mouse. Each method gave good prediction of human PK with parameters predicted within 2-fold. These strategies offer alternative options to the use of cynomolgus monkeys for human PK predictions of linear mAbs, based on in silico methods (typical human popPK parameters) or using a rodent species (Tg32 mouse), and call into question the value of completing extensive in vivo preclinical PK to inform linear mAb PK.

Keywords: FcRn transgenic mouse; Pharmacokinetics; allometric scaling; inter-species scaling; linear clearance; monoclonal antibodies; population pharmacokinetics.

Figure 1.

(a) 2-compartment PK model and (b) algorithm to test for linearity of PK data.

Figure 2.

Distribution of population and individual mAb estimates (with variability) of clearance (CL) in the combined human, cynomolgus monkey and hFcRn Tg32 mouse dataset.

Figure 3.

Distribution of population and individual mAb estimates (with variability) of volume of distribution of the central compartment (V1) in the combined human, cynomolgus monkey and hFcRn Tg32 mouse dataset.

Figure 4.

Median, 5th and 95th percentiles of 200 bootstrap samples with the combined species PK model using the observed dose-normalized concentration (ng/mL) vs. time (hours) data for all of the mAbs in this study. The red lines indicate the concentration vs. time profile of the 5 clinical therapeutic mAbs (bevacisumab, infliximab (for both ankylosing spondylitis and ulcerative colitis), pertuzumab, rituximab and trastuzumab).

Figure 5.

Clearance vs. AC-SINS score for a subset of 11 mAbs in the dataset in human, cynomolgus monkey and hFcRn Tg32 mouse.

Predicted human PK profiles using ‘typical’ human popPK parameter estimates ( ), compared with observed (individual) dose normalized human PK data (symbols) and profiles from fitting human data for individual mAbs ( ).

Figure 7.

Predicted human PK profiles using (a) allometric exponents estimated for Tg32 mouse ( ), (b) allometric exponents estimated for cynomolgus monkey ( ) and (c) ‘typical’ human popPK parameter estimates (). Simulated data is compared with observed (individual) dose normalized human PK data (symbols) and profiles from fitting human data for individual mAbs ( ).