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SynDISCO: A Mechanistic Modeling-Based Framework for Predictive Prioritization of Synergistic Drug Combinations

Sung-Young Shin1,2, Lan K Nguyen3,4

  • 1Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Monash University, Clayton, VIC, Australia. Sungyoung.Shin@monash.edu.

Methods in Molecular Biology (Clifton, N.J.)
|April 19, 2023
PubMed

Insights

Developing effective cancer combination therapies is crucial due to drug resistance. SynDISCO, a computational framework using ordinary differential equation (ODE) modeling, predicts synergistic drug combinations to overcome resistance and improve patient outcomes.

Area of Science:

  • Computational biology
  • Cancer research
  • Systems biology

Background:

  • Cancer monotherapies often face widespread drug resistance, limiting durable clinical benefit.
  • The vast number of potential drug combinations and cancer heterogeneity make experimental testing impractical.
  • Computational approaches are urgently needed to identify and prioritize effective combination treatments.

Purpose of the Study:

  • To present SynDISCO, a computational framework for predicting synergistic anti-cancer drug combinations.
  • To guide the application of SynDISCO for prioritizing combination therapies targeting signaling networks.
  • To demonstrate SynDISCO's utility using the EGFR-MET signaling network in triple-negative breast cancer.

Main Methods:

  • Leveraging mechanistic ordinary differential equation (ODE) modeling to simulate signaling networks.
  • Developing SynDISCO to predict synergistic drug combinations based on ODE models.
  • Applying SynDISCO to the EGFR-MET signaling network as a case study.

Main Results:

  • SynDISCO effectively predicts synergistic drug combinations by modeling underlying biological networks.
  • The framework demonstrated its application in identifying potential combination treatments for triple-negative breast cancer.
  • SynDISCO is a versatile, network- and cancer-independent computational tool.

Conclusions:

  • SynDISCO offers a practical computational approach to identify and prioritize synergistic drug combinations.
  • This framework can accelerate the discovery of novel combination therapies to overcome cancer drug resistance.
  • SynDISCO has broad applicability across different cancer types and signaling networks.
Keywords:
Computational simulationDrug combinationDrug synergyMechanistic modelingODE modelSignaling networkSynDISCO

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