ArticleAssay and drug development technologies2016
Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.
Article in Assay and drug development technologies, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed.
- High-throughput assay for predicting diarrhea risk using a 2D human intestinal stem cell-derived model.Toxicology in vitro : an international journal published in association with BIBRA · 2025Article
- Comparative analysis of Caco-2 cells and human jejunal and duodenal enteroid-derived cells in gel- and membrane-based barrier models of intestinal permeability.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- High-Throughput Assay for Predicting Diarrhea Risk Using a 2D Human Intestinal Stem Cell-Derived Model.bioRxiv : the preprint server for biology · 2024Article
- Exploring the Landscape of Immune Checkpoint Inhibitor-Induced Adverse Events Through Big Data Mining of Pan-Cancer Clinical Trials.The oncologist · 2024Article
- Article
- Decoding kinase-adverse event associations for small molecule kinase inhibitors.Nature communications · 2022Article
- m7G Methylation-Related Genes as Biomarkers for Predicting Overall Survival Outcomes for Hepatocellular Carcinoma.Frontiers in bioengineering and biotechnology · 2022Article
- Effect of SARS-CoV-2 infection on asthma patients.Frontiers in medicine · 2022Article
- Construction and Validation of a m7G-Related Gene-Based Prognostic Model for Gastric Cancer.Frontiers in oncology · 2022Article
- A Synthetic Hydrogel, VitroGelFrontiers in pharmacology · 2021Article
- BIOINTMED: integrated biomedical knowledge base with ontologies and clinical trials.Medical & biological engineering & computing · 2020Article
- Human 3D Gastrointestinal Microtissue Barrier Function As a Predictor of Drug-Induced Diarrhea.Toxicological sciences : an official journal of the Society of Toxicology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov ( https://clinicaltrials.gov/ ), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov . Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs.
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.