Translational m-PBPK Modeling reveals active transcytosis as the pivotal mechanism for nanoparticle tumor delivery: Implications for dose optimization.

The long-held assumption that passive diffusion governs nanomedicine entry into the tumors has been increasingly challenged, with accumulating evidence implicating transcytosis as an important route for nanoparticle transport across the tumor endothelium. However, quantitative comparisons of their relative contributions remain scarce. To address this gap, this study developed a minimal physiologically based pharmacokinetic (m-PBPK) model that integrates in vitro cellular kinetic data to quantitatively describe to tumor delivery of nanoparticles and to assess the relative contributions of diffusion- and transcytosis-mediated transport within a model-based context. The framework was evaluated using PEGylated gold nanoparticles (AuNPs) spanning a range of particle sizes and incorporated empirical size-parameter relationships to enable in vitro-in vivo translational analysis. Model simulations suggested that transcytosis-mediated processes account for the majority of tumor AuNP accumulation under the modeled physiological conditions (99.0 %, 95 % CI: 94.7 %-99.8 %), whereas passive diffusion contributed a smaller fraction under most conditions examined. Dose-dependent analysis further indicated a capacity-limited tumor accumulation behavior, with a threshold around 18 mg, beyond which increasing the dose to 100 mg resulted in only a modest (∼15 %) increase in tumor accumulation. Sensitivity analyses indicated that systemic exposure and endothelial intracellular trafficking behavior are key determinants influencing tumor delivery, whereas enhanced intracellular sequestration consistently reduced tumor accumulation across dose levels. Overall, the proposed m-PBPK framework provides mechanistically interpretable, proof-of-concept insights into nanoparticle tumor delivery, supporting quantitative assessment of transcytosis efficiency and dose-dependent accumulation behavior for hypothesis generation in nanomedicine development.