Power in Numbers: Harnessing Combinatorial and Integrated Screens to Advance Nanomedicine

Natalie Boehnke, Paula T. Hammond

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)12-21
Number of pages10
JournalJACS Au
Issue number1
StatePublished - Jan 24 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 The Authors. Published by American Chemical Society.


  • DNA barcode
  • big data
  • combinatorial screen
  • drug delivery
  • layer-by-layer
  • machine learning
  • nanocarriers
  • nanomedicine
  • omics


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