Significant challenges remain in drug delivery, particularly in targeting hard-to-reach tissues such as solid tumors, which have a dense and complex extracellular matrix (ECM) [1]. Although various drug delivery materials have been developed, the majority involve spherical nanoparticles with diameters ranging from 50 to 500 nm, which face significant physical constraints in effectively penetrating tissues with a dense ECM and small pores [2,3]. While considerable efforts have been devoted to optimizing the chemical properties of nanoparticles, there has been only limited research on how their shape influences drug delivery. Nonetheless, some early studies suggested that more rod-shaped nanoparticles can overcome the limitations of spherical nanoparticles and improve tissue penetration [4,5]. However, there is a lack of comprehensive, head-to-head comparisons showcasing the benefits of rod-shaped nanoparticles in specific applications. The use of this approach has also been impeded by the fact that current rod-shaped nanoparticles (such as carbon nanotubes and gold nanorods) are not biodegradable and are not versatile in terms of the range of drug cargo that they can carry [[6], [7], [8]] .

Herein, we introduce a novel family of rod-shaped nanoparticles derived from DNA-inspired Janus base nanomaterials (JBNs). These nanoparticles are composed of DNA-mimicking bases, specifically guanine and cytosine, conjugated with an amino acid side chain. The unique chemistry, structure, and formation mechanisms of JBNs set them apart from conventional nanomaterials, including lipids, polymers, carbon nanotubes (CNTs), and DNA origami structures. We previously demonstrated that a JBN-based delivery platform (JBNp) could deliver small RNAs into cell via endosomal escape more effectively than conventional lipid nanoparticles (LNPs) could and was more biocompatible than CNTs and cationic polymers [9]. These effects can be attributed to the unique biomimetic structure of JBNps, which results in reduced toxicity and immunogenicity. Moreover, the JBNps are highly versatile in the range of drugs that they can deliver, being applicable for the intracellular delivery of both small chemical molecules and large biological molecules, such as siRNA and mRNA.

In this study, we used a computation-aided design approach to develop rod-shaped Janus base nanoparticles (Rod JBNps) capable of delivering a wide range of cargo, including small molecules and RNAs. Conventional methods for nanoparticle formulation have often relied on a resource-intensive and time-consuming “Edisonian” approach, which is predominantly characterized by trial and error and lacks a systematic and theoretical framework [10,11]. Recent advances in high-fidelity computation-aided design have provided deep insights into the properties and behaviors of nanomaterials, leading to nanoparticle-based drug delivery systems that are more effective and efficient [12,13]. In this paper, we present a streamlined method using computation-aided design to optimize JBNp formulations, in terms of their surface charge, pH, and aging time, to maximize drug loading and delivery. The methodology is theoretically conceptualized and experimentally validated using small-angle X-ray scattering (SAXS), along with a comprehensive in vitro and in vivo evaluations of the ability of JBNps to deliver cargo. Importantly, we also identified that rod-shaped JBNps exhibit superior penetration into ECM-rich adenocarcinoma tumors, achieving significantly deeper infiltration into tumor organoids and solid tumors compared with non-rod shaped JBNps and the FDA-approved spherical nanoparticle, Doxosome. We also applied JBNps to a small animal model as a proof-of-concept and showed that they dramatically enhanced tumor targeting (∼300 %) and improved treatment efficacy compared with Doxosome. These findings highlight the potential of exploiting the physical shape of Rod JBNps to achieve enhanced penetration and targeting of solid tumors. Unlike current antibody-drug conjugate (ADC) strategies, this targeting mechanism relies on physical factors rather than specific tumor antigens [14,15]. Consequently, this approach can overcome the limitations associated with the specificity of tumor surface markers and the heterogeneity of tumor cell expression profiles, offering broader applicability for the targeting of solid tumors. In summary, this study integrates nanoparticle engineering with computation-aided methodology, not only providing a new design strategy for developing shape-based nanoparticle but also demonstrating how computation-aided methods can optimize nanoparticle formulations.