ArticleRSC advances2023
A reliable QSPR model for predicting drug release rate from metal-organic frameworks: a simple and robust drug delivery approach.
Article in RSC advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Article
- Intertumoral and intratumoral barriers as approaches for drug delivery and theranostics to solid tumors using stimuli-responsive materials.Mikrochimica acta · 2024Review
- Topological indices based VIKOR assisted multi-criteria decision technique for lung disorders.Frontiers in chemistry · 2024Article
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Authors and funding
4 authors.
Funding
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Abstract
During the drug release process, the drug is transferred from the starting point in the drug delivery system to the surface, and then to the release medium. Metal-organic frameworks (MOFs) potentially have unique features to be utilized as promising carriers for drug delivery, due to their suitable pore size, high surface area, and structural flexibility. The loading and release of various therapeutic drugs through the MOFs are effectively accomplished due to their tunable inorganic clusters and organic ligands. Since the drug release rate percentage (RES%) is a significant concern, a quantitative structure-property relationship (QSPR) method was applied to achieve an accurate model predicting the drug release rate from MOFs. Structure-based descriptors, including the number of nitrogen and oxygen atoms, along with two other adjusted descriptors, were applied for obtaining the best multilinear regression (BMLR) model. Drug release rates from 67 MOFs were applied to provide a precise model. The coefficients of determination (
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