Mastering the complexities of cancer nanomedicine with text mining, AI and automation

Abstract

In this contribution to the Orations - New Horizons of the Journal of Controlled Release, I present a personal perspective on the complexities of cancer nanomedicine and the approaches to master them. This oration draws mainly from my lab's journey to explore three transformative approaches to master complexities in the field: (1) leveraging text mining to construct dynamic knowledge bases for hypothesis generation in cell-specific drug delivery, (2) introducing the concept of meta-synergy to further optimize and classify multi-drug combinations across dimensions such as chemical loading, pharmacodynamics, and pharmacokinetics (3) utilizing automation to accelerate nanoparticle discovery with advanced screening methodologies such as aggregation-induced emission (AIE). I argue that by embracing complexity in nanomedicine, we can manifest new therapeutic possibilities, paving the way for more effective, precise, and adaptive treatment strategies.