Drug Combination Modeling

Combination effects of compounds are commonly discussed in relation to the treatment of complex and treatment resistance-prone illnesses like cancer, (auto-)immune disorders, and infectious diseases. However, traversing the whole combinatorial space experimentally is infeasible. Therefore, in the last decades, substantially efforts have been made in the field of (predictive) combination modeling. In this reference module, we will discuss the goals of drug combination modeling, the features and endpoints that are used to address combination effect, and the modeling strategies which have been developed. We conclude that data availability is the largest bottle neck in the combination modeling pipeline. Improved data management and availability is essential for drug combination modeling to provide treatment benefit.