Nanoparticles have gained momentum in the world of nanomedicine but face challenges in translation to clinical practice. Today, nanoparticles are the go-to delivery vehicles for a broad range of therapeutic modalities – from chemotherapeutic agents to CRISPR-based drug complexes and mRNA vaccines. However there are only a handful of FDA-approved nanoparticle-based medicines. This lack of clinical progress can be attributed to sub-optimized designs, formulations, and non-uniform clinical responses in patients. Engineering efforts are poised to tackle nanoparticle optimization challenges but are insufficient to address the lack of uniform clinical efficacy. As one can imagine, screening nanoparticle efficacy across a vast heterogeneity of biological barriers in a broad population could mask nanoparticle potential in treating a slightly smaller subset of patients. Therefore, selecting the right patient group can aid in accelerating clinical progress of nanoparticle technology.
Current clinical trial designs do not stratify patients based on their biological affinity to liposomal nanoparticles due to absence of informative biomarkers. The inventors take a data-driven approach to identify the first nanoparticle biomarker that can aid in making such decision to improve clinical efficacy outcome.