ArticleCommunications biology2020
A normalized drug response metric improves accuracy and consistency of anticancer drug sensitivity quantification in cell-based screening.
Article in Communications biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Patient-derived gastric cancer organoids for functional precision oncology: disease-specific bottlenecks and clinical readiness.Translational oncology · 2026Review
- Saudi Patient-Derived Brain and Intracranial Explanted Tumor Cells: Isolation, Growth, and Anticancer Drug Screening.International journal of molecular sciences · 2026Article
- Deciphering the Role of Cancer Stem Cells in Breast Cancer Brain Colonization Using a Novel Patient-Derived Model.Advanced healthcare materials · 2026Article
- A Classifier for Patient-Derived Colorectal Tumoroid Drug Sensitivity Using Confocal Imaging and Growth Rate Inhibition Metrics.Cancer research communications · 2026Article
- VUScope: a mathematical model for evaluating image-based drug response measurements and predicting long-term incubation outcomes.Bioinformatics (Oxford, England) · 2026Article
- Development and validation of the Normalized Organoid Growth Rate (NOGR) metric in brightfield imaging-based assays.Communications biology · 2024Article
- Recent advances in and applications of ex vivo drug sensitivity analysis for blood cancers.Blood research · 2024Review
- CRISPR/Cas9-edited ROS1 + non-small cell lung cancer cell lines highlight differential drug sensitivity in 2D vs 3D cultures while reflecting established resistance profiles.Journal of translational medicine · 2024Article
- High-content screening of drug combinations of an mPGES-1 inhibitor in multicellular tumor spheroids leads to mechanistic insights into neuroblastoma chemoresistance.Molecular oncology · 2024Article
- Robust scoring of selective drug responses for patient-tailored therapy selection.Nature protocols · 2024Review
- Single-organoid analysis reveals clinically relevant treatment-resistant and invasive subclones in pancreatic cancer.NPJ precision oncology · 2023Article
- Reassessing pharmacogenomic cell sensitivity with multilevel statistical models.Biostatistics (Oxford, England) · 2023Article
- OrBITS: label-free and time-lapse monitoring of patient derived organoids for advanced drug screening.Cellular oncology (Dordrecht, Netherlands) · 2023Article
- Auranofin Synergizes with the PARP Inhibitor Olaparib to Induce ROS-Mediated Cell Death in Mutant p53 Cancers.Antioxidants (Basel, Switzerland) · 2023Article
- Deep learning methods for drug response prediction in cancer: Predominant and emerging trends.Frontiers in medicine · 2023Review
- Gaseous nitric oxide tumor ablation induces an anti-tumor abscopal effect.Cancer cell international · 2022Article
- A cross-study analysis of drug response prediction in cancer cell lines.Briefings in bioinformatics · 2022Article
- Using mathematical modeling to estimate time-independent cancer chemotherapy efficacy parameters.In silico pharmacology · 2022Article
- Nitro-Deficient Niclosamide Confers Reduced Genotoxicity and Retains Mitochondrial Uncoupling Activity for Cancer Therapy.International journal of molecular sciences · 2021Article
- PTD4 Peptide Increases Neural Viability in an In Vitro Model of Acute Ischemic Stroke.International journal of molecular sciences · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
Accurate quantification of drug effects is crucial for identifying pharmaceutically actionable cancer vulnerabilities. Current cell viability-based measurements often lead to biased response estimates due to varying growth rates and experimental artifacts that explain part of the inconsistency in high-throughput screening results. We developed an improved drug scoring model, normalized drug response (NDR), which makes use of both positive and negative control conditions to account for differences in cell growth rates, and experimental noise to better characterize drug-induced effects. We demonstrate an improved consistency and accuracy of NDR compared to existing metrics in assessing drug responses of cancer cells in various culture models and experimental setups. Notably, NDR reliably captures both toxicity and viability responses, and differentiates a wider spectrum of drug behavior, including lethal, growth-inhibitory and growth-stimulatory modes, based on a single viability readout. The method will therefore substantially reduce the time and resources required in cell-based drug sensitivity screening.
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