Numerical estimation of drug loading contents in amphiphilic nanogels

Abstract

Amphiphilic nanogels (ANGs) are promising colloidal carriers to improve bioavailability of poorly water-soluble drugs. In contrast to conventional hydrophilic nanogels, ANGs contain additional hydrophobic domains in their network to load hydrophobic cargos. However, optimizing drug loading remains labour-intensive due to the lack of quantitative tools that accurately capture the complex ANG–drug interactions. To address this limitation and assess drug compatibility, we developed a quantitative framework based on Flory–Huggins interaction parameters (χ). Key to our approach is the empirical adjustment of the correction factor α to account for unequal contributions of dispersion forces, polar interactions, and hydrogen bonds. Using a model ANG and a library of hydrophobic drugs and dyes, we established selection rules for α based on the dominant interaction type: α = 1 for dispersion-dominated, α = 0.7 for polar, and α = 0.3 for hydrogen bond-dominated systems. This enabled systematic grouping of cargos and revealed strong monotonic negative correlations between adjusted χ values and experimental loading capacities. The resulting universal calibration curve links χ to drug loading content across diverse ANG–drug systems. Consequently, our framework suggests predictive potential of solubility parameter-based models, reduces experimental burden, and supports the rational design of ANG carriers tailored to specific hydrophobic drugs.