ReviewNature reviews. Drug discovery2023
Applications of single-cell RNA sequencing in drug discovery and development.
Review in Nature reviews. Drug discovery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 247 papers, 1 of them a synthesis that pooled it.
What it found
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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
247 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- A tri-scale in silico framework integrating pharmacovigilance and mechanistic modeling suggests tepotinib-associated acute kidney injury risk.Renal failure · 2026Article
- Multi‑omics insights into uveitis: From mechanisms to precision medicine (Review).International journal of molecular medicine · 2026Review
- Artificial intelligence in biomarker discovery for diseases: diagnostic and therapeutic prospects.Signal transduction and targeted therapy · 2026Review
- Single-cell and spatial transcriptomics reveals the spatiotemporal trajectory of the small peptide TAP4 in delaying postharvest fruit senescence.Plant communications · 2026Article
- GEM-GPT Enables Personalized Cell Type-Resolved Therapeutic Design for Systems Pharmacology.bioRxiv : the preprint server for biology · 2026Article
- Dynamic cellular programs of human cardiac allograft rejection revealed by spatial transcriptomics.Nature cardiovascular research · 2026Article
- Data-centric feedback loops for next-generation immunotherapy development.Nature biomedical engineering · 2026Review
- scKanFormer: A Transformer-KAN framework with biologically informed attention for cell type annotation in large-scale scRNA-seq data.PLoS computational biology · 2026Article
- Multi-Omics-Guided Design and Safety Engineering of Nucleic Acid Therapeutics: From Molecular Perturbation to Predictive Toxicology and Precision Translation.Chemical biology & drug design · 2026Review
- Machine Learning-Based Identification of Molecular Signatures in PTOA Cell Subtypes via Single-Cell Transcriptomics in a Mouse Model.Stem cell reviews and reports · 2026Article
- Article
- Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.Journal of ovarian research · 2026Review
- Single-cell RNA sequencing profiles drug activity within spatially engineered 3D cultures.Nature communications · 2026Article
- Unveiling a unique microglial phenotype promoting oxidation in the iBRB: insights from single-cell transcriptomics in the NPDR rat model.Cell & bioscience · 2026Article
- Integrative single-cell and spatial transcriptomic analysis reveals that ATG13 enriched in cancer-associated fibroblasts is associated with the suppression of ferroptosis in colorectal cancer.Discover oncology · 2026Article
- Causal effect estimation from trans-regulatory single-cell CRISPR screens.Cell genomics · 2026Review
- PPP1R14A in male erectile dysfunction: key role in smooth muscle cells.Sexual medicine · 2026Article
- Beyond chromatin accessibility: bulk ATAC-seq as an integrative assay to portray genomes and epigenomes.NAR genomics and bioinformatics · 2026Article
- Design of Single-Atom Nanozymes for Precision Treatment of Erectile Dysfunction with Integrated Single-Cell RNA Sequencing and Machine Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
187 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.
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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.