Mathematical modeling study identifies logistic model with ratio-dependent drug efficacy as best fit for NSCLC dynamics

Summary

This study evaluates which mathematical models best capture the eco-evolutionary dynamics of non-small cell lung cancer (NSCLC) by fitting two-population models to in-vitro data tracking drug-sensitive and drug-resistant cells. The researchers compared growth models (logistic, Gompertz, von Bertalanffy) and drug efficacy terms (Norton-Simon, linear, ratio-dependent) using data from conditions with and without Alectinib and cancer-associated fibroblasts (CAFs). The logistic model with ratio-dependent drug efficacy best fit monoculture data. Key findings include that CAFs promote coexistence between resistant and sensitive cells, while Alectinib leads to competitive exclusion, and that growth parameters remained stable across CAF conditions while competition and drug efficacy parameters shifted.