Design of multi-drug combinations for poly-pharmacological effects using composition-activity relationship modeling and multi-objective optimization approach: Application in traditional Chinese medicine

In recent years, multi-component therapies are increasingly utilized to treat complex diseases such as cancer, diabetes, and other chronic complex diseases. Here, we proposed the protocol for rational design of drug combination with poly-pharmacological effects by integration of design of experiments (DOE), computational modeling, and multiple-objective optimization algorithm. Here, we introduce a common workflow for modeling quantitative relationship of chemical composition and multiple activities of drug combinations. As an example, anti-oxidation, neuroprotective, and anti-platelet activities of three different salvia polyphenols were measured, which were mathematically represented by multivariant regression models to evaluate the effect of combination. In validation, the optimized combination which obtained by weighed-sum method showed good activities in all three models. Our results demonstrate that the multiple-objective optimization strategy is suitable to optimize the ratio of the compounds so to induce the best therapeutic action.