A Multiscale QSP Model Compares Tumor Payload Exposure for Three MMAE ADCs
The model links systemic pharmacokinetics, cellular disposition and tumor distribution. Combining predicted free-payload exposure with in vitro cytotoxicity reproduced the observed efficacy ranking of three ADCs in xenograft models.
Connecting Systemic Exposure with Tumor Distribution
A university-based team developed a quantitative systems pharmacology (QSP) model for early comparison of antibody–drug conjugates (ADCs). The model combines systemic pharmacokinetics, single-cell disposition and tumor distribution to estimate exposure to unconjugated monomethyl auristatin E (MMAE) inside tumors.
The authors applied it to RC48, RC108 and RC118, three valine-citrulline–MMAE ADCs directed at different antigens. Xenograft-mouse data served as the experimental reference. Reported errors for intratumoral free-MMAE exposure ranged from −38.13% to 20.52%.
Using Exposure and Cytotoxicity Together
The team simulated tumor payload exposure and spatial distribution at an ADC dose of 1.5 mg/kg. Combining these outputs with in vitro cytotoxicity measurements, expressed as IC50, reproduced the observed efficacy ranking of the three ADCs.
Global sensitivity analysis identified target density, ADC permeability and payload uptake, efflux and permeability as important drivers of intratumoral exposure. The reported evaluation used xenograft data; the authors propose replacing selected inputs with human-relevant parameters in future applications.