ReviewGenome medicine2016
Approaches to modernize the combination drug development paradigm.
Review in Genome medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed.
- Identifying Factors Associated with the Acquisition of Multiple Indications for Anticancer Drugs.Current oncology (Toronto, Ont.) · 2026Observational
- A systematic study of parameter sharing strategies in multi-task learning for drug synergy and sensitivity prediction.Journal of computer-aided molecular design · 2026Article
- UniSyn: a multi-modal framework with knowledge transfer for anti-cancer drug synergy prediction.Genome biology · 2026Article
- Hgtsynergy: a transfer learning method for predicting anticancer synergistic drug combinations based on a drug-drug interaction heterogeneous graph.BMC bioinformatics · 2026Article
- KGLGANSynergy: knowledge graph-based local and global attention network for drug synergy prediction.Journal of translational medicine · 2025Article
- Old drugs, new challenges: reassigning drugs for cancer therapies.Cellular & molecular biology letters · 2025Review
- Exploring two tumor treatment strategies: effectiveness of ribosome inactivating proteins and mesenchymal stem cells/MSC derived extracellular vesicles in cancer treatment.Frontiers in oncology · 2025Review
- SynDRep: a synergistic partner prediction tool based on knowledge graph for drug repurposing.Bioinformatics advances · 2025Article
- Bayesian sequential monitoring strategies for trials of digestive cancer therapeutics.BMC medical research methodology · 2024Article
- Unlocking hidden potential: advancements, approaches, and obstacles in repurposing drugs for cancer therapy.British journal of cancer · 2024Review
- Predicting anticancer synergistic drug combinations based on multi-task learning.BMC bioinformatics · 2023Article
- Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models.Nature biomedical engineering · 2023Article
- Codelivery of Phytochemicals with Conventional Anticancer Drugs in Form of Nanocarriers.Pharmaceutics · 2023Review
- A cellular and molecular biology-based update for ivermectin against COVID-19: is it effective or non-effective?Inflammopharmacology · 2023Review
- High Expression of Microtubule-associated Protein TBCB Predicts Adverse Outcome and Immunosuppression in Acute Myeloid Leukemia.Journal of Cancer · 2023Article
- In Vitro/In Vivo Translation of Synergistic Combination of MDM2 and MEK Inhibitors in Melanoma Using PBPK/PD Modelling: Part I.International journal of molecular sciences · 2022Article
- NEXGB: A Network Embedding Framework for Anticancer Drug Combination Prediction.International journal of molecular sciences · 2022Article
- A review of deep learning applications in human genomics using next-generation sequencing data.Human genomics · 2022Review
- Metabolomics-based phenotypic screens for evaluation of drug synergy via direct-infusion mass spectrometry.iScience · 2022Article
- From cell lines to cancer patients: personalized drug synergy prediction.Bioinformatics (Oxford, England) · 2022Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in genomic sequencing and omics-based capabilities are uncovering tremendous therapeutic opportunities and rapidly transforming the field of cancer medicine. Molecularly targeted agents aim to exploit key tumor-specific vulnerabilities such as oncogenic or non-oncogenic addiction and synthetic lethality. Additionally, immunotherapies targeting the host immune system are proving to be another promising and complementary approach. Owing to substantial tumor genomic and immunologic complexities, combination strategies are likely to be required to adequately disrupt intricate molecular interactions and provide meaningful long-term benefit to patients. To optimize the therapeutic success and application of combination therapies, systematic scientific discovery will need to be coupled with novel and efficient clinical trial approaches. Indeed, a paradigm shift is required to drive precision medicine forward, from the traditional "drug-centric" model of clinical development in pursuit of small incremental benefits in large heterogeneous groups of patients, to a "strategy-centric" model to provide customized transformative treatments in molecularly stratified subsets of patients or even in individual patients. Crucially, to combat the numerous challenges facing combination drug development-including our growing but incomplete understanding of tumor biology, technical and informatics limitations, and escalating financial costs-aligned goals and multidisciplinary collaboration are imperative to collectively harness knowledge and fuel continual innovation.
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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.