Understanding nano-engineered particle-cell interactions: biological insights from mathematical models
Stuart T Johnston1,2,3, Matthew Faria2,3,4, Edmund J Crampin2,3,5
1School of Mathematics and Statistics, University of Melbourne Parkville Victoria 3010 Australia stuart.johnston@unimelb.edu.au.
Nanoscale Advances
|September 22, 2022
Summary
Quantitative models help design nano-engineered particles for medicine by linking particle properties to cell interaction and uptake rates. Standardized reporting advances this field.
Area of Science:
- Biomedical Engineering
- Nanotechnology
- Computational Biology
Background:
- Understanding nano-engineered particle interactions with cells is crucial for developing effective therapeutic, diagnostic, and imaging agents.
- The rate of cell interaction and internalization is directly influenced by the physicochemical properties of nanoparticles.
Purpose of the Study:
- To review mathematical and computational models used to study particle-cell interactions and internalization.
- To elucidate the relationship between particle properties and cellular uptake kinetics.
- To highlight advances in understanding particle internalisation mechanisms through modeling.
Main Methods:
- Review of various mathematical and computational modeling approaches.
- Detailed explanation of the mathematical methodology for each model type.
- Analysis of model benefits, limitations, and applications to experimental data.
Main Results:
- Models provide a powerful tool for understanding particle-cell interaction and internalization mechanisms.
- Application of models to experimental data has advanced understanding of particle internalisation.
- Standardized experimental reporting is essential for maximizing the potential of modeling approaches.
Conclusions:
- Quantitative models are vital for the rational design of nano-engineered particles.
- Future research requires hybrid experimental and theoretical investigations to address complex questions in particle-cell interactions.
- Community adoption of standardized reporting is a key step towards unlocking the full potential of modeling.
