Understanding intracellular transport processes pertinent to synthetic gene delivery via stochastic simulations and sensitivity analyses.

A major challenge in synthetic gene delivery is to quantitatively predict the optimal design of polymer-based gene carriers (polyplexes). Here, we report a consistent, integrated, and fundamentally grounded computational methodology to address this challenge. This is achieved by accurately representing the spatio-temporal dynamics of intracellular structures and by describing the interactions between gene carriers and cellular components at a discrete, nanoscale level. This enables the applications of systems tools such as optimization and sensitivity analysis to search for the best combination of systems parameters. We validate the approach using DNA delivery by polyethylenimine as an example. We show that the cell topology (e.g., size, circularity, and dimensionality) strongly influences the spatiotemporal distribution of gene carriers, and consequently, their optimal intracellular pathways. The model shows that there exists an upper limit on polyplexes' intracellular delivery efficiency due to their inability to protect DNA until nuclear entry. The model predicts that even for optimally designed polyethylenimine vectors, only approximately 1% of total DNA is delivered to the nucleus. Based on comparison with gene delivery by viruses, the model suggests possible strategies to significantly improve transfection efficiencies of synthetic gene vectors.