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Kinetics and Mechanism of Camptothecin Release from Transferrin-Gated Mesoporous Silica Nanoparticles through a pH-Responsive Surface Linker.

Nicolás JacksonAndrea C OrtizAlejandro JerezJavier MoralesFrancisco Arriagada
Published in: Pharmaceutics (2023)
Stimuli-responsive nanomaterials have emerged as a promising strategy for inclusion in anticancer therapy. In particular, pH-responsive silica nanocarriers have been studied to provide controlled drug delivery in acidic tumor microenvironments. However, the intracellular microenvironment that the nanosystem must face has an impact on the anticancer effect; therefore, the design of the nanocarrier and the mechanisms that govern drug release play a crucial role in optimizing efficacy. Here, we synthesized and characterized mesoporous silica nanoparticles with transferrin conjugated on their surface via a pH-sensitive imine bond (MSN-Tf) to assess camptothecin (CPT) loading and release. The results showed that CPT-loaded MSN-Tf (MSN-Tf@CPT) had a size of ca. 90 nm, a zeta potential of -18.9 mV, and a loaded content of 13.4%. The release kinetic data best fit a first-order model, and the predominant mechanism was Fickian diffusion. Additionally, a three-parameter model demonstrated the drug-matrix interaction and impact of transferrin in controlling the release of CPT from the nanocarrier. Taken together, these results provide new insights into the behavior of a hydrophobic drug released from a pH-sensitive nanosystem.
Keyphrases
  • drug delivery
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  • machine learning
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  • deep learning
  • solid state