Partition-controlled drug release from polymeric nanocapsules: A physically consistent framework with...

Mathematical models for drug release from polymeric nanocapsules have traditionally relied on Noyes-Whitney-based first-order kinetics, which implicitly predict faster release for drugs exhibiting higher solubility in the oily core. This prediction is inconsistent with numerous experimental observations in which more lipophilic compounds are released more slowly. To address this apparent paradox, a partition-controlled kinetic framework is derived in which the effective release rate scales inversely with oily-core solubility. The resulting model, [Formula: see text] introduces a dimensionless correction factor α and a reference solubility S₀, yielding a dimensionally consistent formulation while preserving the mechanistic inverse-solubility dependence predicted by partition equilibrium arguments. A re-analysis of the previously published nanocapsule model reveals a dimensional inconsistency and a tabulation error affecting the reported kinetic parameters. After correction, the published adapalene data are found to be consistent with the proposed inverse-solubility scaling. The model is further evaluated using four release datasets (adapalene in two oily cores, capsaicin, and dihydrocapsaicin), yielding R² values between 0.925 and 0.969 with C_max fixed at the final experimental value. These results support partition-controlled release as a physically plausible and dimensionally consistent framework for describing drug release from polymeric nanocapsules.