ReviewNature reviews. Drug discovery2021
Improving target assessment in biomedical research: the GOT-IT recommendations.
Review in Nature reviews. Drug discovery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers, 4 of them syntheses that pooled it.
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
105 citing papers in PubMed, 4 syntheses or guidelines pooled it, 199 citations in OpenAlex.
- Systematic review and meta-analysis of genome-wide pooled CRISPR screens to identify host factors involved in influenza A virus infection.Journal of virology · 2024Pooled it
- Systematic literature review reveals suboptimal use of chemical probes in cell-based biomedical research.Nature communications · 2023Pooled it
- Screening for in vitro systematic reviews: a comparison of screening methods and training of a machine learning classifier.Clinical science (London, England : 1979) · 2023Pooled it
- Recommendations for robust and reproducible preclinical research in personalised medicine.BMC medicine · 2023Guideline
- On-chip 3D potency assay for prediction of clinical outcomes for cell therapy candidates for osteoarthritis.Nature communications · 2025Trial
- Key regulatory elements of the TGFβ-LRRC15 axis predict disease progression and immunotherapy resistance across cancer types.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Plant-Derived Natural Products and Selective Apoptosis: A Cancer-Cell Vulnerability-State Framework from Redox Imbalance to Membrane-Ion Dysregulation.Pharmaceuticals (Basel, Switzerland) · 2026Review
- A Comprehensive Understanding ofCurrent issues in molecular biology · 2026Review
- Translational assessment instruments for preclinical to first-in-human decision-making: a scoping review.Journal of translational medicine · 2026Article
- A generalizable computational framework for integrating heterogeneous biomarkers into interpretable scalar risk representations.BMC medical informatics and decision making · 2026Article
- Beyond Urease: New Potential Enzymatic Targets inACS omega · 2026Review
- Article
- Black-box data: a new paradigm for biomedicine in the AI era.Chemical science · 2026Review
- Trichomonas vaginalis Drug Targets and Their Role in Drug Discovery and Development.Pharmaceutical research · 2026Review
- AI-powered TargetMap: Enabling system-level target discovery through full-path reasoning on a unified knowledge graph.iScience · 2026Article
- Review
- Genomics of drug target prioritization for complex diseases.Nature reviews. Genetics · 2026Review
- singIST: An integrative method for comparative single-cell transcriptomics between disease models and humans.PLoS computational biology · 2026Article
- Alzheimer's disease and memantine effects on NMDA-receptor blockade: non-invasive in vivo insights from magnetoencephalography.Molecular psychiatry · 2026Article
- Building a credibility-based framework for target discovery: Perspectives from tRNA synthetase-linked metabolic diseases.Briefings in bioinformatics · 2026Article
45 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
11 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Academic research plays a key role in identifying new drug targets, including understanding target biology and links between targets and disease states. To lead to new drugs, however, research must progress from purely academic exploration to the initiation of efforts to identify and test a drug candidate in clinical trials, which are typically conducted by the biopharma industry. This transition can be facilitated by a timely focus on target assessment aspects such as target-related safety issues, druggability and assayability, as well as the potential for target modulation to achieve differentiation from established therapies. Here, we present recommendations from the GOT-IT working group, which have been designed to support academic scientists and funders of translational research in identifying and prioritizing target assessment activities and in defining a critical path to reach scientific goals as well as goals related to licensing, partnering with industry or initiating clinical development programmes. Based on sets of guiding questions for different areas of target assessment, the GOT-IT framework is intended to stimulate academic scientists' awareness of factors that make translational research more robust and efficient, and to facilitate academia-industry collaboration.
Indexed as
Identifiers
What OpenQuestion holds
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.