Computation-aided design of rod-shaped nanoparticles for tumoral targeting.

Various nanomaterials have been developed for drug delivery, but the vast majority are spherical nanoparticles (50-500 nm in diameter). This limits their ability to target and infiltrate hard-to-penetrate tissues, such as certain solid tumors with a dense extracellular matrix (ECM). To investigate how the key physical parameter of shape influences tumor targeting, we developed Janus base nanoparticles (JBNps), a family of rod-shaped delivery vehicles that self-assemble into nanotube bundles with encapsulated drug cargos. In a head-to-head comparison with spherical nanoparticles, the rod-shaped JBNps enabled significantly better tumor infiltration and targeting (by 300 %) of an ECM-rich adenocarcinoma model. To efficiently optimize formulations, we employed a computation-aided methodology to refine drug loading and design parameters, which achieved maximal drug loading efficiency (by 97 %). This work provides a broadly applicable strategy for designing nanoparticles and highlights the potential of exploiting the physical shape of nanoparticles to achieve enhanced penetration and targeting of solid tumors.