## 4 Discussion  
The previous research on electroporation optimization focused mostly on the empirical determination of input parameters that describe electric field or single characteristics of the medium [31]. However, the relationship between the input parameters and the therapeutic outcome is indirect, as the final state of the system is achieved over time due to the redistribution of the constituents induced by biophysical processes. For this reason, the response of the system to the external trigger (e.g., electric field) leads to different outcomes (e.g., electroporation efficiency). However, output parameters describe the system dynamics more precisely, making them more suitable to estimate the efficiency [32]. In our case, the output parameter is the distance between the electroporated membrane and the plasmid, which incorporates not only plasmid DNA concentration, but also the cell size and concentration. As such, it allows for more precise characterization of the system than the input parameter (plasmid DNA concentration). This helps to determine optimal conditions for electroporation as the output parameter directly exhibits the dynamics of the system. Therefore, plotting the distance value, which is non-linearly related to the plasmid concentration, versus transfection efficiency (see Figure 5A) reveals new results that are masked in the original representation of the results (see Figure 1A). Namely, there is a sigmoidal dependency between the distance value and the number of transfected cells, and the latter is most sensitive to the distance value in the 0.22-0.4 \(\upmu\)m region. When the distance is higher or lower, this sensitivity is lost, causing the lag and stationary parts of the graph. Plotting the distance against cell viability (See Figure 5B) reveals stationary part when the distance value is above \(\sim\)0.3 \(\upmu\)m, and the cell viability starts decreasing at lower distances irrespectively of the pulse number. This implies that \(\sim\)0.3 \(\upmu\)m is a threshold below which the DNA induces negative effect on cell viability. Additionally, the sigmoidal part of the curve illustrates a clear three stage biophysical process with lag, linear, and saturation phases. The presence of the transition state/point of the curves (Figure 5A,B) allow to clearly differentiate between the therapeutic strategies, depending on the particular necessities of the therapy: i) choose DNA concentration in the range corresponding to the distances \(>\)\(\sim\)0.2 \(\upmu\)m and achieve the cell transfection efficiency while preserving high cell viability (in overall \(>\)\(\sim\)45%) or ii) increase plasmid DNA concentration (corresponding distance \(<\)\(\sim\)0.2 \(\upmu\)m) to induce high cell death (in overall \(<\)\(\sim\)45%) for maximal anticancer effect by killing the cancerous cells. The increase in transfection efficiency when the distance is lowered can be explained by the increased efficiency of electrophoresis. It is well known that the interaction of plasmid DNA and electroporated membrane to form DNA/membrane complex is essential for successful electrotransfection [9; 15; 33]. The electrophoretic force depends on the strength, number, and duration of the applied electric field. In turn, the magnitude of the electrophoretic force is one of the factors that determine the electrophoretic motility of the charged molecules [34; 35]. A highly charged molecule, such as a plasmid, will move a certain distance once affected with a specific electric pulse [28]. However, with increase of plasmid concentration, the distance between the plasmids decreases (see Figure 4), and therefore lower electric field parameters might be required to achieve the same amount of plasmids reaching the cell due to electrophoresis. The application of more electric pulses for electrotransfection increases the lifetime of the electropores as well as the electrophoretic force induced by the electric field. Therefore, the distance plasmid DNA can migrate from to form the DNA/membrane complex is larger.