Nanoparticle Optimization for Enhanced Targeted Anticancer Drug Delivery

This study applies rigorous optimization to the design of NPs. A preliminary investigation revealed that delivery efficiency increases monotonically witha and AR. However, maximizinga and AR results in nonuniform drug distribution, which impairs tumor regression. Therefore, a multiobjective optimization (MO) problem is formulated to quantify the trade-off between NPs accumulation and distribution. The MO is solved using the derivative-free mesh adaptive direct search algorithm. Theoretically, the Pareto-optimal set consists of an infinite number of mathematically equivalent solutions to the MO problem. However, interesting design solutions can be identified subjectively, e.g., the ellipsoid with a major axis of 720  nm and an aspect ratio of 7.45, as the solution closest to the utopia point. The MO problem formulation is then extended to optimize NP biochemical properties: ligand–receptor binding affinity and ligand density. Optimizing physical and chemical properties simultaneously results in optimal desi gns with reduced NP sizes and thus enhanced cellular uptake. The presented study provides an insight into NP structures that have potential for producing desirable drug delivery.
Source: Journal of Biomechanical Engineering - Category: Biomedical Engineering Source Type: research