In Silico modeling for assessment of the most effective ratio and interaction of anticancer drugs

Mathematical models are widely used to assess drug synergy. However, identifying the most effective combination ratio represents a major challenge. In this study, we applied two established mathematical models to assess synergism and optimize the ratio of vorinostat (SAHA) and doxorubicin (DOX) in vitro for breast cancer (BC) models. BC poses a significant challenge in oncology due to high incidence rates, mortality, and drug resistance. Therefore, developing new treatment strategies is essential to improve anticancer therapeutic outcomes. While polychemotherapy offers significant clinical benefits by enhancing efficacy and reducing toxicity, no consensus exists on optimal drug ratio determination. We evaluated synergism across a broad panel of BC cell lines using the Bliss model and the Chou-Talalay method. Both methods identified a similar pattern of combination synergism. Based on synergy index calculations and drug ratio determination, we found the Bliss model more suitable for determining the optimal SAHA/DOX ratio. The most effective drugs ratio was calculated as 30:1 of SAHA to DOX, respectively. This combination showed strong efficacy in both 2D and 3D cancer models. Our results highlight the potential value of synergy-based computational tools to guide effective combination therapies in BC and justify further preclinical and in vivo validation of the SAHA/DOX combination.