The development of precise quantitative metrics is essential for characterizing the response of biological systems to external perturbations, enabling a transition from qualitative observation to predictive modeling. In this context, mathematical frameworks can provide insight into the dynamic behavior of cell populations under external stimuli. In this study, a logistic-type growth model was employed to describe wound healing dynamics. A scratch assay protocol was applied to lung cancer cells, and a perturbation-based analytical framework was developed to quantify the influence of external factors. Novel metrics were introduced, including the percentage difference in wound closure at specific time points, the shift in inflection time, and the Average Difference in Wound Closure (ADWC). A pilot experimental study was conducted to evaluate the effect of Low-Level Laser Therapy (LLLT) on cell migration. The proposed model successfully captured the nonlinear dynamics of wound closure and enabled quantitative comparison between control and treated groups. The analysis demonstrated that LLLT enhances cellular activity, leading to a shift in the inflection time by approximately 7.6 h and an increase of 25.4% in wound closure at 24 h compared to the control group. The ADWC metric further confirmed a systematic difference in the overall healing dynamics between conditions. The presented perturbation-based framework provides a rigorous and interpretable tool for quantifying the effects of external stimuli on biological systems. These findings suggest a light-dependent modulation of tumor cell migration in an in vitro model, indicating that light exposure may influence cellular behavior under certain conditions. This observation may be relevant for clinical applications involving light, such as photodynamic therapy, particularly in cases of incomplete drug delivery.
Kontomaris et al. (Mon,) studied this question.