ArticleNature communications2021
MuSyC is a consensus framework that unifies multi-drug synergy metrics for combinatorial drug discovery.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.
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Who cites it
61 citing papers in PubMed, 1 synthesis or guideline pooled it, 103 citations in OpenAlex.
- Dietary Interventions with Polyphenols in Osteoarthritis: A Systematic Review Directed from the Preclinical Data to Randomized Clinical Studies.Nutrients · 2021Pooled it
- Quantitative Systems Pharmacology Model Predicts Enhanced Antitumor Efficacy of Combined Cytotoxic T‑Lymphocyte-Associated Protein 4 (CTLA-4) and Programmed Cell Death Protein 1 (PD-1) Blockade in a Syngeneic Mouse Model of Breast Cancer.ACS pharmacology & translational science · 2026Article
- DeepSynBa: actionable drug combination prediction with complete dose-response profiles.Bioinformatics (Oxford, England) · 2026Article
- A novel combination therapy for ER+ breast cancer suppresses drug resistance via an evolutionary double-bind.Molecular systems biology · 2026Article
- Development and characterization of triazole-based WDR5 inhibitors for the treatment of glioblastoma.JCI insight · 2026Article
- Fpr1p mediates the synergistic effect of rapamycin or tacrolimus with caspofungin inJAC-antimicrobial resistance · 2026Article
- Article
- Rethinking the role of synergy calculations in the next century of drug combination discovery.Med (New York, N.Y.) · 2026Review
- Mechanism-based prediction of drug synergy via network controllability analysis of therapeutic pathways in intractable diseases.iScience · 2026Article
- A shape-constrained regression and wild bootstrap framework for reproducible drug synergy testing.bioRxiv : the preprint server for biology · 2026Article
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- Innovative In Vitro-In Silico Platform for Dose-Response Modeling in Canine Bladder Cancer: A 3D Organoid- and Mathematics-Based Approach.The AAPS journal · 2026Article
- High-Resolution Quantification of Two-Way Nanobody Synergy Using Automated Liquid Handling and Computational Modeling.Bio-protocol · 2026Article
- Combination of oxidative phosphorylation and platelet-derived growth factor inhibitors for the treatment of ovarian cancers.npj women's health · 2026Article
- Prediction of mixture toxicity of essential oil constituents using nonparametric and parametric models against Musca domestica L.Pest management science · 2025Article
- SOS1 inhibition suppresses the emergence of osimertinib resistance to generate a durable response inScience signaling · 2025Article
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- PanThera: predictive analysis of higher-order combination therapies using deep neural networks.Briefings in bioinformatics · 2025Article
- Systems Biology of the Cancer Cell.Annual review of biomedical engineering · 2025Review
1 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Drug combination discovery depends on reliable synergy metrics but no consensus exists on the correct synergy criterion to characterize combined interactions. The fragmented state of the field confounds analysis, impedes reproducibility, and delays clinical translation of potential combination treatments. Here we present a mass-action based formalism to quantify synergy. With this formalism, we clarify the relationship between the dominant drug synergy principles, and present a mapping of commonly used frameworks onto a unified synergy landscape. From this, we show how biases emerge due to intrinsic assumptions which hinder their broad applicability and impact the interpretation of synergy in discovery efforts. Specifically, we describe how traditional metrics mask consequential synergistic interactions, and contain biases dependent on the Hill-slope and maximal effect of single-drugs. We show how these biases systematically impact synergy classification in large combination screens, potentially misleading discovery efforts. Thus the proposed formalism can provide a consistent, unbiased interpretation of drug synergy, and accelerate the translatability of synergy studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.