New Approach for Determining Nanomaterial (NM) Biodistribution in the Body Offers an Alternative to Animal Testing

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Schematic overview of the UCF approach to predict the biodistribution of nanomaterials in the body.
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Researchers
Edward Price, Ph.D.
Andre Gesquiere, Ph.D.
External Link (sciences.ucf.edu)
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Andrea Adkins
Assistant Director 407.823.0138
Patent Protection

US Patent Pending
Publications
An In Vitro Assay and Artificial Intelligence Approach to Determine Rate Constants of Nanomaterial-Cell Interactions
Scientific Reports , 2019;9(1):13943. Published 2019 Sep 26. doi:10.1038/s41598-019-50208-x

System with predictive computer modeling enables nanomaterial drug screening tests that effectively measure NM-cell interactions in vivo.

Researchers at the University of Central Florida have developed a new system to quantify and accurately predict the biodistribution of nanomaterials (NMs) in the body, reducing the need for animal studies. Using a novel quantitative fluorescence-based in vitro assay and computational models, the UCF system provides in vivo whole-body predictive modeling with cellular level resolution. The new system is also faster and more cost-efficient than conventional testing methods.

As industries such as medicine, electronics and agriculture increase their use of nanomaterials, the ability to quantify and assess the actual tissue and cellular level dose of NMs in the body is vital. Unfortunately, current methods still rely on animal testing, requiring in vivo tissue samples to be collected and analyzed postmortem. Such processes are also time-consuming and expensive, as they may use substantial numbers of animal subjects (in many instances, only one time point is available per animal). Additionally, tissue homogenization of resected tissues is destructive to cells and tissue architecture, resulting in the loss of important cellular-level information.

Technical Details

The UCF invention comprises a system design and methods for producing a mechanistic in vivo simulation PBPK (physiologically-based pharmacokinetic) model that accurately quantifies and predicts the biodistribution of a variety of NMs in animals. It includes a high-throughput ratiometric corrected fluorescence (RCF) assay (in vitro) that measures the effects of cell-induced and media-induced loss of fluorescence from the NMs. The assay also accounts for the fact that NMs interact with cells mainly through activated transport, not passive diffusion. Information collected from the assay feeds a cell kinetics simulation model, which uses a novel Genetic Algorithm (GA) to extract rate kinetics from the NM-cell interactions. Outputs from the GA become inputs to an in vivo PBPK simulation model that accounts for tissue volume, cellular compositions of issues, blood flow rates, vessel fenestrations and kinetics of cell-NM interactions. This combination of in vitro and in silico methods enables accurate, quantifiable predictions of in vivo NM biodistribution across tissues of the whole body with cellular resolution.

Benefits

  • Accurately quantifies NM accumulation
  • Reduces cost
  • Offers an alternative to animal testing in NM distribution
  • Provides resolution at the cellular level

Applications

  • Nanomaterial drug screening
  • Agricultural nanomaterial compound screening