High-Throughput Flow Cytometry Drug Combination Discovery with Novel Synergy Analysis Software, SynScreen

Area of Science:

• Pharmacology
• Computational Biology
• Drug Discovery

Background:

• Classical drug therapies face challenges like toxicity, low efficacy, and drug resistance.
• Synergistic drug combinations offer potential for lower, tolerable dosages and restored drug sensitivity.

Purpose of the Study:

• To develop and present SynScreen, a software application for identifying synergistic drug combinations.
• To enable visual and mathematical determination of compound concentrations yielding super-additive effects.

Main Methods:

• SynScreen employs nonlinear regression to fit dose-response data.
• Synergism is assessed using Bliss independence and Loewe additivity models.
• The software was validated using in vitro high-throughput flow cytometry (HTFC) screens and open-source datasets.

Main Results:

• SynScreen visually depicts experimental measurements against theoretical Bliss additivity surfaces.
• The software automatically exports graphical and tabular summaries of drug interactions.
• Validation with existing datasets confirmed SynScreen's applicability and utility.

Conclusions:

• SynScreen facilitates the visual assessment of large datasets for rapid identification of effective drug combinations.
• The software streamlines the process of discovering synergistic drug combinations.
• SynScreen supports the design of confirmatory studies and clinical trials for novel combination therapies.