SynergyFinder 2.0: visual analytics of multi-drug combination synergies.

Tero Aittokallio,Anil K Giri,Aleksandr Ianevski

doi:10.1093/nar/gkaa216

Abstract

SynergyFinder (https://synergyfinder.fimm.fi) is a stand-alone web-application for interactive analysis and visualization of drug combination screening data. Since its first release in 2017, SynergyFinder has become a widely used web-tool both for the discovery of novel synergistic drug combinations in pre-clinical model systems (e.g. cell lines or primary patient-derived cells), and for better understanding of mechanisms of combination treatment efficacy or resistance. Here, we describe the latest version of SynergyFinder (release 2.0), which has extensively been upgraded through the addition of novel features supporting especially higher-order combination data analytics and exploratory visualization of multi-drug synergy patterns, along with automated outlier detection procedure, extended curve-fitting functionality and statistical analysis of replicate measurements. A number of additional improvements were also implemented based on the user requests, including new visualization and export options, updated user interface, as well as enhanced stability and performance of the web-tool. With these improvements, SynergyFinder 2.0 is expected to greatly extend its potential applications in various areas of multi-drug combinatorial screening and precision medicine.

Highlights

Drug combinations have become a standard therapy for various complex diseases, including tuberculosis, malaria, HIV, and most of the advanced cancers [1,2,3,4,5]
The degree of combination synergy, or antagonism, is quantified by comparing the observed drug combination response against the expected response, calculated using a reference model that assumes no interaction between drugs
Based on the users’ requests, SynergyFinder 2.0 implements novel and improved analysis and visualization options for multi-drug combination data, including automated outlier detection procedure, extended curve-fitting functionality, statistical assessment of replicate measurements, as well as many other enhancements appearing in the latest implementation of SynergyFinder

Summary

INTRODUCTION

Drug combinations have become a standard therapy for various complex diseases, including tuberculosis, malaria, HIV, and most of the advanced cancers [1,2,3,4,5]. Easy-to-use tools that enable unbiased identification of synergistic combinations from high-throughput experimental data are highly needed for systematic and reproducible discovery process To address this need, we implemented SynergyFinder [13], a web-application that enables researchers to preprocess, analyze and visualise pairwise drug combinations in an interactive manner. A so-called R-CHOP therapy that involves five drugs is an approved curative therapy for Diffuse Large B-Cell Lymphoma [30] The search for such higher-order synergistic combinations by industry and academia has led to the generation of dose–response data for a large number of multi-drug combinations [31]. There is a need for a software tool that cannot only assess synergy/antagonism of a large number of multi-drug combinations, and enable an interactive exploration of the synergy patterns for an unbiased analysis of higher-order drug combination experiments. Based on the users’ requests, SynergyFinder 2.0 implements novel and improved analysis and visualization options for multi-drug combination data, including automated outlier detection procedure, extended curve-fitting functionality, statistical assessment of replicate measurements, as well as many other enhancements appearing in the latest implementation of SynergyFinder

MATERIALS AND METHODS

CONCLUSIONS