ReviewNature reviews. Drug discovery2017
Opportunities and challenges in phenotypic drug discovery: an industry perspective.
Review in Nature reviews. Drug discovery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 410 papers.
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.
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Who cites it
410 citing papers in PubMed.
- Differential posttraumatic stress disorder symptom cluster response to stellate ganglion block: secondary analysis of a randomized controlled trial.Translational psychiatry · 2024Trial
- Drug-likeness prioritised selection identifies anti-Journal of enzyme inhibition and medicinal chemistry · 2026Article
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- New approach methodologies: drug screening platform to identify antifibrotic compounds.Nature protocols · 2026Review
- FuTCM-PDD: a multi-level information fusion framework integrating KAN modeling and AutoML for phenotype-based drug discovery from Traditional Chinese Medicine.Chinese medicine · 2026Article
- Technology profiles in FDA-approved new molecular entities, 2013-2024: a latent class analysis.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026Article
- A computational framework for proteome-wide target profiling of natural products: mechanistic and therapeutic insights into ginsenosides.Briefings in bioinformatics · 2026Article
- From Executor to Orchestrator: The Pharmacology Scientist in the Age of Agentic AI.Clinical pharmacology and therapeutics · 2026Review
- Leveraging Morphological Profiling for Mechanistic Elucidation of Metal-Based Anticancer Compounds.JACS Au · 2026Article
- Integrating single-cell and bulk transcriptomic perturbation resources reveals complementary therapeutic spaces for drug repurposing.bioRxiv : the preprint server for biology · 2026Article
- Antibacterial drug discovery: challenges and preclinical promises from synthetic small molecules.Chemical Society reviews · 2026Review
- Deep phenotypic profiling uncovers cryptic effects of antifilarial drugs.PLoS pathogens · 2026Article
- Review
- Bridging the phenotype-target gap for molecular generation via multi-objective reinforcement learning.Bioinformatics (Oxford, England) · 2026Article
- Deep-learning-based virtual screening of antibacterial compounds.Nature biotechnology · 2026Article
- A comprehensive pharmacological survey across heterogeneous patient-derived glioblastoma stem cell models.iScience · 2026Article
- Genetically supported drug target prioritization for rare diseases.Genome medicine · 2026Article
- An Agentic Platform for Drug Repurposing Unified across Molecular, Phenotypic, and Clinical Scales.bioRxiv : the preprint server for biology · 2026Article
- Review
- Development of Water-Trapping Pyrrole-2-carboxylic Acids as Broad-Spectrum Metallo-β-lactamase Inhibitors.Journal of medicinal chemistry · 2026Article
350 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phenotypic drug discovery (PDD) approaches do not rely on knowledge of the identity of a specific drug target or a hypothesis about its role in disease, in contrast to the target-based strategies that have been widely used in the pharmaceutical industry in the past three decades. However, in recent years, there has been a resurgence in interest in PDD approaches based on their potential to address the incompletely understood complexity of diseases and their promise of delivering first-in-class drugs, as well as major advances in the tools for cell-based phenotypic screening. Nevertheless, PDD approaches also have considerable challenges, such as hit validation and target deconvolution. This article focuses on the lessons learned by researchers engaged in PDD in the pharmaceutical industry and considers the impact of 'omics' knowledge in defining a cellular disease phenotype in the era of precision medicine, introducing the concept of a chain of translatability. We particularly aim to identify features and areas in which PDD can best deliver value to drug discovery portfolios and can contribute to the identification and the development of novel medicines, and to illustrate the challenges and uncertainties that are associated with PDD in order to help set realistic expectations with regard to its benefits and costs.
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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.