On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach

Abstract

Objectives of the present investigation were: (1) to compare three literature reported tumor growth inhibition (TGI) pharmacodynamic (PD) models and propose an optimal new model that best describes the xenograft TGI data for antibody drug conjugates (ADC), (2) to translate efficacy of the ADC Trastuzumab-emtansine (T-DM1) from mice to patients using the optimized PD model, and (3) to apply the translational strategy to predict clinically efficacious concentrations of a novel in-house anti-5T4 ADC, A1mcMMAF. First, the performance of all four of the PD models (i.e. 3 literature reported + 1 proposed) was evaluated using TGI data of T-DM1 obtained from four different xenografts. Based on the estimates of the pharmacodynamic/pharmacokinetic (PK/PD) modeling, a secondary parameter representing the efficacy index of the drug was calculated, which is termed as the tumor static concentration (TSC). TSC values derived from all four of the models were compared with each other, and with literature reported values, to assess the performance of these models. Subsequently, using the optimized PK/PD model, PD parameters obtained from different cell lines, human PK, and the proposed translational strategy, clinically efficacious doses of T-DM1 were projected. The accuracy of projected efficacious dose range for T-DM1 was verified by comparison with the clinical doses. Aforementioned strategy was then applied to A1mcMMAF for projecting its efficacious concentrations in clinic. TSC values for A1mcMMAF, obtained by fitting TGI data from 4 different xenografts with the proposed PK/PD model, were estimated to range from 0.6 to 11.5 μg mL⁻¹. Accordingly, the clinically efficacious doses for A1mcMMAF were projected retrospectively. All in all, the improved PD model and proposed translational strategy presented here suggest that appropriate correction for the clinical exposure and employing the TSC criterion can help translate mouse TGI data to predict first in human doses of ADCs.

Application of a PK-PD Modeling and Simulation-Based Strategy for Clinical Translation of Antibody-Drug Conjugates: a Case Study with Trastuzumab Emtansine (T-DM1)

“…Thus, this step serves as a validation step for the tumor distribution model of ADC. Using the molecular size specific parameters for antibody and small molecule distribution into the tumor, our model has been able to a priori predict the tumor exposures for multiple ADCs in the past (brentuximab-vedotin (12), A1mcMMAF (10)), including T-DM1 (14). …”

“…Growth of the tumor was modeled using an equation proposed by Haddish-Berhane et al (12), which is a modification of the original cell distribution model proposed by Simeoni et al (18). When the tumor is small, the growth is characterized mainly using the exponentially function Kg Ex , and as the tumor grows, the model switches from exponential growth to linear growth (Kg Lin ).…”

“…The term “ e ” refers to the allometric exponent used to scale up the parameter from monkeys to humans. In case of mAb (TTmAb/T-DM1), exponent value of “1” was used for all the PK parameters, as per our previous report (12). In case of small molecule (DM1), however, exponent of “0.75” was used for CL and CLD and “1” was used for V1 and V2.…”

Antibody–Drug Conjugates as Cancer Therapeutics: Past, Present, and Future

“…In another study, an optimized PD model describing xenograft tumor growth inhibition data translated adotrastuzumab emtansine efficacy from mice to patients. 81 The translational strategy was then applied to predict clinically efficacious FIH doses of a novel ADC.…”

Prediction of non-linear pharmacokinetics in humans of an antibody-drug conjugate (ADC) when evaluation of higher doses in animals is limited by tolerability: Case study with an anti-CD33 ADC

“…16-19 Moreover, understanding the effect of the site of conjugation, drug loading, and drug-linker design on ADC PK has enabled mitigation of accelerated clearance observed with some ADCs. 20-22 Mechanistic PK/pharmacodynamic (PD) 23-26 and multi-scale models 13-15 have been proposed to improve translatability from preclinical species to the clinic. However, implementation and calibration of these multi-scale models require a substantial amount of in vitro and in vivo data that may not be available when human PK predictions are first required, which is typically during early stages of drug development.…”