ReviewClinical pharmacology and therapeutics2016
Leveraging big data to transform target selection and drug discovery.
Review in Clinical pharmacology and therapeutics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 1 of them a synthesis 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
72 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis and review of in silico methods in drug discovery - part 1: technological evolution and trends from big data to chemical space.The pharmacogenomics journal · 2025Pooled it
- Article
- Harnessing transcriptomics for discovery of natural products to overcome acquired cancer resistance.Archives of pharmacal research · 2026Review
- HIV Pharmacology Data Repository: Setting the New Information-Sharing Standard for Clinical and Preclinical Pharmacokinetic Studies.Clinical pharmacology and therapeutics · 2025Review
- Data Exploration for Target Predictions Using Proprietary and Publicly Available Data Sets.Chemical research in toxicology · 2025Article
- Large-scale information retrieval and correction of noisy pharmacogenomic datasets through residual thresholded deep matrix factorization.Briefings in bioinformatics · 2025Article
- Interaction between post-tumor inflammation and vascular smooth muscle cell dysfunction in sepsis-induced cardiomyopathy.Frontiers in immunology · 2025Article
- RNA-Seq-Based Transcriptome Analysis of Chinese Cordyceps Aqueous Extracts Protective Effect against Adriamycin-Induced mpc5 Cell Injury.International journal of molecular sciences · 2024Article
- Protein target similarity is positive predictor of in vitro antipathogenic activity: a drug repurposing strategy for Plasmodium falciparum.Journal of cheminformatics · 2024Article
- Serum Proteomic Signatures of Common Health Outcomes among Older Adults.Gerontology · 2024Article
- Advances in Protein-Ligand Binding Affinity Prediction via Deep Learning: A Comprehensive Study of Datasets, Data Preprocessing Techniques, and Model Architectures.Current drug targets · 2024Review
- Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes.Current rheumatology reports · 2023Review
- Large-Scale Databases and Portals on Cancer Genome to Analyze Chaperone Genes Correlated to Patient Prognosis.Methods in molecular biology (Clifton, N.J.) · 2023Article
- BETA: a comprehensive benchmark for computational drug-target prediction.Briefings in bioinformatics · 2022Article
- Computational drug repurposing based on electronic health records: a scoping review.NPJ digital medicine · 2022Article
- Application of Artificial Intelligence in Discovery and Development of Anticancer and Antidiabetic Therapeutic Agents.Evidence-based complementary and alternative medicine : eCAM · 2022Review
- Potential Biomarkers for Liver Cancer Diagnosis Based on Multi-Omics Strategy.Frontiers in oncology · 2022Review
- Systematic transcriptome analysis reveals molecular mechanisms and indications of bupleuri radix.Frontiers in pharmacology · 2022Article
- Recent Advances in Cancer Drug Discovery Through the Use of Phenotypic Reporter Systems, Connectivity Mapping, and Pooled CRISPR Screening.Frontiers in pharmacology · 2022Review
- PromisingFrontiers in immunology · 2022Review
12 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
2 authors.
Funding
Abstract
The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and clinical research have dramatically increased the types of data available to the public. The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine.
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.