Nanocarriers have
significant potential to advance personalized
medicine through targeted drug delivery. However, to date, efforts
to improve nanoparticle accumulation at target disease sites have
largely failed to translate clinically, stemming from an incomplete
understanding of nano–bio interactions. While progress has
been made to evaluate the effects of specific physical and chemical
nanoparticle properties on trafficking and uptake, there is much to
be gained from controlling these properties singularly and in combination
to determine their interactions with different cell types. We and
others have recently begun leveraging library-based nanoparticle screens
to study structure–function relationships of lipid- and polymer-based
drug delivery systems to guide nanoparticle design. These combinatorial
screening efforts are showing promise in leading to the successful
identification of critical characteristics that yield improved and
specific accumulation at target sites. However, there is a crucial
need to equally consider the influence of biological complexity on
nanoparticle delivery, particularly in the context of clinical translation.
For example, tissue and cellular heterogeneity presents an additional
dimension to nanoparticle trafficking, uptake, and accumulation; applying
imaging and screening tools as well as bioinformatics may further
expand our understanding of how nanoparticles engage with cells and
tissues. Given recent advances in the fields of omics and machine
learning, there is substantial promise to revolutionize nanocarrier
development through the use of integrated screens, harnessing the
combinatorial parameter space afforded both by nanoparticle libraries
and clinically annotated biological data sets in combination with
high throughput
in vivo
studies.