(M-009) Combined multi-analyte population PK modeling of ABBV-400, a novel c-Met targeting ADC

Carla Biesdorf de Almeida, n/a – Associate Director Clinical Pharmacology, AbbVie Inc.; Sven Mensing, n/a – Senior Director, Head of Pharmacometrics, AbbVie Inc.; Apurvasena Parikh, n/a – Director, AbbVie Inc.; Benjamin Engelhardt, n/a – Associate Director Pharmacometrics, AbbVie Inc.

Objectives: ABBV-400 is an ADC consisting of a c-Met-targeting antibody (telisotuzumab [ABT-700]) conjugated to a potent Top1 inhibitor payload. c-Met is a cell surface tyrosine kinase encoded by the MET gene and is overexpressed on the surface of tumor cells.
ABBV-400 is being evaluated in multiple trials, including an ongoing Phase 1, first-in-human, proof of concept, open-label, dose escalation, dose expansion study in subjects with advanced solid tumors (NCT05029882). Preliminary NCA [1] have shown nonlinear pharmacokinetics (PK) across the dose range studied.
The purpose of this analysis was to build a combined multi-analyte population PK model to characterize the PK of ABBV-400 conjugate, total antibody and Top1i payload and the associated inter-individual variability (IIV).

Methods: ABBV-400 conjugate, total antibody and Top1i payload (free A-1743332) concentrations were available from 204 subjects from the Phase 1 study across doses of 1.6 mg/kg to 6.0 mg/kg Q3W. Model development was conducted in NONMEM 7.5.1 using Stochastic Approximation Expectation-Maximization and Monte Carlo importance sampling estimation methods.
Different clearance and variability models were evaluated. A covariate analysis was performed using different patient characteristics. Graphical model evaluation techniques, such as goodness-of-fit plots and visual predictive checks were used to assess model performance.

Results: The final model assumed a heterogeneous mixture of varying isotype species of drug to antibody ratio, with each isotope following a 2-compartment model and the same PK parameters. ABBV-400 elimination was assumed to occur by deconjugation or by clearance via linear and non-linear kinetics resulting in payload release reflecting the more than dose proportional PK of the conjugate. Payload PK was assumed to follow a one compartment model with linear elimination process.
IIV on clearance and central volume of the conjugate was estimated to be 0.539 (84.5 %CV) and 0.0505 (22.8%). An allometric weight effect on clearance and the central volume for the conjugate was tested and fixed to the values of 0.75 and 1, respectively [2]. Covariate testing revealed sex as significant covariate for conjugate peripheral volume and clearance, payload central volume and payload clearance, albumin on conjugate clearance and central volume, and bilirubin and age on payload clearance.

Conclusions: A population PK multi-compartment model was successfully developed to describe ABBV-400 conjugate, total antibody and Top1i payload concentrations over time. Due to the complex nature of the Top1i payload and ABBV-400 conjugate concentration profiles a multi-compartment model was necessary and superior to separate 2 compartment models for Top1i payload and ABBV-conjugate. PK simulations show that the effect of covariates on exposures were small (approximately ≤ 25%).

Citations: [1] Biesdorf, C. et. al. (2024). Clinical pharmacokinetics of ABBV-400, a novel c-Met-targeting antibody drug conjugate, in patients with advanced solid tumors. [Poster Abstract] ASCPT
[2] Anderson, B. J., & Holford, N. H. (2009). Mechanistic basis of using body size and maturation to predict clearance in humans. Drug metabolism and pharmacokinetics, 24(1), 25-36.