The promise of multidrug therapies for cancer has evoked renewed interest in high-throughput methods to identify effective drug combinations. Although a cell-based, large-scale single-drug screening strategy is well established, its extension to drug combination screening becomes cost-prohibitive. Our group aims to computationally predict the therapeutic effects of drug combinations, and thereby enable in silico screening of large repertories of drug combinations to prioritize potential effective multi-drug therapies for further experimental validation. It could dramatically revolutionize the current procedure of multi-drug therapy discovery and lead to the rapid identification of new combination therapies.

We developed a novel Drug-Induced Genomic Residual Effect (DIGRE) computational model to predict drug combination effects by explicitly modeling the drug response dynamics and gene expression changes after individual drug treatments. The DIGRE model won the best performance in the National Cancer Institute’s DREAM 7 Drug Combination Synergy Prediction Challenge, an international crowdsourcing-based computational challenge for predicting drug combination effects using transcriptome data. This challenge’s blind-assessment of submitted computational models revealed that the prediction of drug pair activity from DIGRE was significantly consistent with the vast majority of the organizers’ experimental validations. In addition, we further validated our DIGRE model using another experimental dataset. Consequently, DIGRE could potentially be used for large-scale discovery of effective drug combinations for further experimental validation, possibly leading to the rapid identification of new therapies for complex diseases.

The code for DIGRE model:

Download the psudo code for DIGRE model here

Download the source code of DIGRE model here

There are three steps in DIGRE model.

Step One

To show the derivation of the similarity score (r) between drug A and B from their genomic profiles.

Step Two

To depict the estimation procedure of the drug-induced genomic residual effect from the similarity score,

Step Three

To show the model for the final synergy score.