Abstract LB442: Whole body PBPK/PD modeling to support first-in-human dose selection for GenSci140, a potential best-in-class FRα biparatopic ADC, in patients with cancer

Abstract Background: GenSci140 is a novel FRα-directed biparatopic ADC by featuring a cleavable linker conjugated to a topoisomerase I inhibitor as payload. FRα displays limited expression in normal tissues but is overexpressed in epithelial cancers (e. g. , ovarian, non-small cell lung, and endometrial carcinomas). Preclinical studies have showed its broad-spectrum antitumor activity across multiple xenograft models. To support dose selection for first-in-human (FIH) study (NCT07251166), a multiscale whole body physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model was developed to predict the effective dose range in patients with advanced solid tumors. Methods: The multiscale PBPK/PD model was constructed using PK-Sim®, MoBi®, and R softwares, integrating systemic pharmacokinetics (PK) of the ADC, its payload and naked antibody (nAb) with the key steps, including FcRn-mediated recycling, biparatopic FRα target binding, crosslinking internalization, intracellular trafficking, payload release, and the subsequent tumor growth inhibition (TGI). The model also integrated the synthesis and degradation of FRα, and the competitive binding dynamics between the ADC and nAb for FRα across tumor and various healthy tissues. Physiological parameters were utilized to enable cross-species translation. Monkey PBPK model for GenSci140 and clinical PBPK model for Elahere (monospecific ADC targeting FRα) were constructed to estimate human FRα expression across tissues. Mouse PBPK/PD models of GenSci140 were developed using plasma PK of ADC, total antibody (Tab) and payload, along with TGI data from ovarian cancer (OVCAR-3) and lung cancer (NCI-H441) cell-derived xenograft (CDX) models, to inform human TGI parameters. These multiscale parameters were integrated into a comprehensive whole-body PBPK/PD model for cancer patients. Virtual clinical trial simulations were subsequently performed to predict GenSci140 PK and efficacy result. Results: The monkey PBPK model accurately described the plasma PK of GenSci140 ADC, Tab and payload across tested doses. Clinical PBPK models for Elahere successfully simulate observed plasma PK in patients at multiple dose levels. The mouse PBPK/PD model for GenSci140 effectively simulated plasma PK and TGI data in CDX models. Using proposed human PBPK/PD model, the efficacious does range for patients was projected, with efficacy defined as the dose achieving 100% TGI relative to baseline tumor size. Conclusions: The whole body PBPK/PD model mechanistically elucidated the mode of action of GenSci140 and established a robust PK/TGI relationship. It provided a quantitative basis for identifying clinically effective doses and informed FIH dose selection. This model will be incorporated into a broader disease platform to guide dose expansion and ongoing clinical optimization as trial data accrue. Citation Format: Fan Zhang, Yehua Xie, Guangli Ma, Xiao Liang, Xumin Zhao, Yihui Lin, Xuan Ye, Peng Qi, Xiaozhen Wang, Haizhou Zhang, Shu Zhang, Siqin Wang, Lei Jin. Whole body PBPK/PD modeling to support first-in-human dose selection for GenSci140, a potential best-in-class FRα biparatopic ADC, in patients with cancer abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts) ; 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86 (8Suppl): Abstract nr LB442.