Simulation Based Analysis of Nanocarrier Internalization: Exciting Challenges with a New Computational Tool - Intracellular Delivery: Fundamentals and Applications - page 151

Figure 13 illustrates the change in the drug transient components, involved in the
various delivery routes. It demonstrates the lack of exocytosis. The change of the
nanovehicle containing components is in accordance with the slow degradation
inside the cell. The receptor containing components converge either to the equilib-
rium value or to zero. The slowest processes are the decomposition of cyt_NV and
lys_NV_L_D.

5 Conclusions

A new computational tool has been employed for the model-based analysis of the
endocytosis and exocytosis mechanisms involved in nanocarrier delivery. It is to be
emphasized that we made a quite hypothetical study, because at this moment the
available data are not sufficient for a sophisticated identification of the underlying
process model.
We demonstrated a hypothetical computation in the analysis of a significant,
practical problem. Computational models may be a useful interacting partner for the
field expert. The case studies allow studying the individual mechanisms, as well as
the synergistic and antagonistic effects of their combinations. It helps to understand,
the possible limiting transportations and transformations, as well as how inherent
degradation limits the utilization of the injected drug. In addition, by switching on
and off the respective processes, we can evaluate the effects of some deleting certain
pathways, like exocytosis of the nanocarrier or of the drug containing nanocarrier.
The applied methodology proved to be flexible and effective enough to describe
and to run complex process models without any mathematical and computational
assistance.
The most interesting general conclusions can be summarized, as follows.

5.1 Limiting Assumptions vs. Constructive Usefulness

All of the computer simulations, especially the completely hypothetical ones, can
be evaluated by the balance between assumptions and usefulness. The question is
whether constructive applications can compensate for the possible malfunctions,
caused by the limiting assumptions.
First, we describe the explicit and implicit assumptions behind our model. We
assumed the following:

1. The modeled components, transportations and transformations cover all of the
necessary and sufficient elements determining the states and transitions of
the studied reality.
2. There are not hidden, un-modeled components, affecting the modeled
transitions.