Advancing Cancer Drug Delivery with Nanoparticles: Challenges and Prospects in Mathematical Modeling for In Vivo and In Vitro Systems

Simple Summary

Cancer treatment can be improved by using tiny particles, called nanoparticles, to deliver drugs directly to cancer cells. To understand how these drug-loaded nanoparticles work in the body, researchers create mathematical models that predict their behavior. These models help us understand how different factors—like the size and makeup of nanoparticles, the characteristics of tumors, and the body’s own responses—affect the treatment’s success. However, current models sometimes make assumptions that may not match what happens in real-life scenarios, causing us to overestimate the treatment’s effectiveness. This research aims to refine these mathematical models by incorporating more realistic data and advanced artificial intelligence techniques. These improvements may lead to more accurate predictions and ultimately make nanoparticle-based cancer treatments more successful in clinical settings, benefiting patients and advancing the field of cancer therapy.