ArticleNature communications2020
Computationally predicting clinical drug combination efficacy with cancer cell line screens and independent drug action.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
47 citing papers in PubMed, 75 citations in OpenAlex.
- Deciphering the Mechanisms of Statin-Ezetimibe Drug Combinations Using Boolean Logical Modeling and Transcriptomic Data.CPT: pharmacometrics & systems pharmacology · 2026Article
- Additivity, Not Synergy, Underlies the Efficacy of Current Combination Regimens in Urothelial Cancer.Cancer research communications · 2026Article
- Rethinking the role of synergy calculations in the next century of drug combination discovery.Med (New York, N.Y.) · 2026Review
- UniSyn: a multi-modal framework with knowledge transfer for anti-cancer drug synergy prediction.Genome biology · 2026Article
- Data Mining for Identification of Targets and Repurposed Drugs to Eliminate Persistent Chronic Myeloid Leukaemia Stem Cells: Targeting RAS/RAF Signalling.Oncology research · 2026Article
- Novel Mixed Cancer-Cell Models Designed to Capture Inter-Patient Tumor Heterogeneity for Accurate Evaluation of Drug Combinations.International journal of molecular sciences · 2025Article
- Combined XPO1 Inhibition and Parthenolide Treatment Can Be Efficacious in Treating Triple-Negative Breast Cancer.International journal of molecular sciences · 2025Article
- Machine Learning for Multi-Target Drug Discovery: Challenges and Opportunities in Systems Pharmacology.Pharmaceutics · 2025Review
- The Combination of HSP90 Inhibitors and Selumetinib Reinforces the Inhibitory Effects on Plexiform Neurofibromas.Cancers · 2025Article
- Immune organoid for cancer immunotherapy.Acta pharmaceutica Sinica. B · 2025Review
- Heterogeneous therapy-resistant cancer cells have distinct and exploitable drug sensitivity profiles.bioRxiv : the preprint server for biology · 2025Article
- Scaling up drug combination surface prediction.Briefings in bioinformatics · 2025Article
- Predicting drug combination response surfaces.npj drug discovery · 2025Article
- Drug discovery for chemotherapeutic resistance based on pathway-responsive gene sets and its application in breast cancer.Frontiers in bioinformatics · 2025Article
- Prediction of cancer cell line-specific synergistic drug combinations based on multi-omics data.PeerJ · 2025Article
- Discovery, Validation and Mechanistic Study of XPO1 Inhibition in the Treatment of Triple-Negative Breast Cancer.Cancers · 2024Article
- DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations.Briefings in bioinformatics · 2024Article
- A pan-cancer screen identifies drug combination benefit in cancer cell lines at the individual and population level.Cell reports. Medicine · 2024Article
- Ultrasensitive Response Explains the Benefit of Combination Chemotherapy Despite Drug Antagonism.Molecular cancer therapeutics · 2024Article
- Integration of Pan-Cancer Cell Line and Single-Cell Transcriptomic Profiles Enables Inference of Therapeutic Vulnerabilities in Heterogeneous Tumors.Cancer research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Evidence has recently emerged that many clinical cancer drug combinations may derive their efficacy from independent drug action (IDA), where patients only receive benefit from the single most effective drug in a drug combination. Here we present IDACombo, an IDA based method to predict the efficacy of drug combinations using monotherapy data from high-throughput cancer cell line screens. We show that IDACombo predictions closely agree with measured drug combination efficacies both in vitro (Pearson's correlation = 0.93 when comparing predicted efficacies to measured efficacies for >5000 combinations) and in a systematically selected set of clinical trials (accuracy > 84% for predicting statistically significant improvements in patient outcomes for 26 first line therapy trials). Finally, we demonstrate how IDACombo can be used to systematically prioritize combinations for development in specific cancer settings, providing a framework for quickly translating existing monotherapy cell line data into clinically meaningful predictions of drug combination efficacy.
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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.