Modelling the impact of temperature on nanocarrier behavior: Thermodynamics, structural transitions, and drug release

Thermo-responsive polymeric nanoparticles represent one of the most powerful classes of smart drug delivery systems, thanks to their ability to translate temperature variations into precisely regulated drug-release responses. Unlike conventional carriers, where temperature acts merely as a kinetic accelerator, thermo-responsive nanocarriers exploit temperature as an active control parameter capable of inducing structural, thermodynamic, and transport transitions within the delivery system. The release for these systems can be rationally modulated through three fundamental mechanisms: temperature-accelerated degradation and erosion of biodegradable matrices, temperature-dependent transport processes governed by diffusion and solubility, and switch-like release triggered by thermo-induced structural transitions such as lower critical solution temperature (LCST)/ upper critical solution temperature (UCST)-driven polymer collapse or lipid bilayer melting. This work critically examines how temperature alters carrier architecture, polymer-solvent interactions, and internal transport pathways, and how these changes can be explicitly captured through mathematical modelling. Empirical, semi-empirical, and fully mechanistic modelling frameworks are systematically discussed, highlighting their strengths, limitations, and physical interpretability. Particular emphasis is placed on models that couple temperature to nanoparticle geometry, polymer thermodynamics, and diffusion dynamics, enabling a predictive description of release behavior and continuous modulation regimes. This article proposes a rational design for next-generation thermo-responsive nanocarriers, in which polymer chemistry, nanoparticle structure, experimental characterization, and mechanistic modelling are integrated from the earliest stages of material development. By unifying thermo-responsive material design with physically meaningful release models, this review aims to provide both a conceptual framework and a practical toolbox for the development of smart nanomedicines whose temperature-dependent behavior can be predicted.