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.