AI Article Synopsis
- - This study enhances the "Nano-Tumor Database" by expanding time-dependent data sets for nanoparticles (NPs) in tumors from 376 to 534, while also increasing total data points from 1732 to 2345 across nearly 300 studies from 2005 to 2021.
- - It reveals that the median tumor delivery efficiency of nanoparticle treatments is only 0.67% of the injected dose, which aligns with previous findings, though higher delivery efficiencies of over 3% are hypothesized based on modeling data.
- - The research also provides insights on the distribution of nanoparticles in healthy organs, highlighting that the liver shows the highest accumulation, and offers perspectives on improving nanoparticle design and clinical applications
Article Abstract
Low tumor delivery efficiency is a critical barrier in cancer nanomedicine. This study reports an updated version of "Nano-Tumor Database", which increases the number of time-dependent concentration data sets for different nanoparticles (NPs) in tumors from the previous version of 376 data sets with 1732 data points from 200 studies to the current version of 534 data sets with 2345 data points from 297 studies published from 2005 to 2021. Additionally, the current database includes 1972 data sets for five major organs (i.e., liver, spleen, lung, heart, and kidney) with a total of 8461 concentration data points. Tumor delivery and organ distribution are calculated using three pharmacokinetic parameters, including delivery efficiency, maximum concentration, and distribution coefficient. The median tumor delivery efficiency is 0.67% injected dose (ID), which is low but is consistent with previous studies. Employing the best regression model for tumor delivery efficiency, we generate hypothetical scenarios with different combinations of NP factors that may lead to a higher delivery efficiency of >3%ID, which requires further experimentation to confirm. In healthy organs, the highest NP accumulation is in the liver (10.69%ID/g), followed by the spleen 6.93%ID/g and the kidney 3.22%ID/g. Our perspective on how to facilitate NP design and clinical translation is presented. This study reports a substantially expanded "Nano-Tumor Database" and several statistical models that may help nanomedicine design in the future.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10604101 | PMC |
| http://dx.doi.org/10.1021/acsnano.3c04037 | DOI Listing |
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