ReviewClinical pharmacology and therapeutics2009
Data-driven methods to discover molecular determinants of serious adverse drug events.
Review in Clinical pharmacology and therapeutics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- Extraction of Information Related to Drug Safety Surveillance From Electronic Health Record Notes: Joint Modeling of Entities and Relations Using Knowledge-Aware Neural Attentive Models.JMIR medical informatics · 2020Article
- Higher plasma bilirubin predicts veno-occlusive disease in early childhood undergoing hematopoietic stem cell transplantation with cyclosporine.World journal of transplantation · 2016Article
- A curated and standardized adverse drug event resource to accelerate drug safety research.Scientific data · 2016Article
- Integrating Multiple Evidence Sources to Predict Adverse Drug Reactions Based on a Systems Pharmacology Model.CPT: pharmacometrics & systems pharmacology · 2015Article
- A time-indexed reference standard of adverse drug reactions.Scientific data · 2014Article
- Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity.The pharmacogenomics journal · 2014Article
- A semi-supervised approach to extract pharmacogenomics-specific drug-gene pairs from biomedical literature for personalized medicine.Journal of biomedical informatics · 2013Article
- Novel data-mining methodologies for adverse drug event discovery and analysis.Clinical pharmacology and therapeutics · 2012Review
- Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.Journal of the American Medical Informatics Association : JAMIA · 2012Article
- Automatic filtering and substantiation of drug safety signals.PLoS computational biology · 2012Article
- Discovery and preclinical validation of drug indications using compendia of public gene expression data.Science translational medicine · 2011Article
- S3QL: a distributed domain specific language for controlled semantic integration of life sciences data.BMC bioinformatics · 2011Article
- Predicting adverse drug reactions using publicly available PubChem BioAssay data.Clinical pharmacology and therapeutics · 2011Article
- Exploring off-targets and off-systems for adverse drug reactions via chemical-protein interactome--clozapine-induced agranulocytosis as a case study.PLoS computational biology · 2011Article
- Article
- Molecular therapy drives patient-centric health care paradigms.Clinical and translational science · 2010Article
- Pharmacogenetic testing and therapeutic drug monitoring are complementary tools for optimal individualization of drug therapy.European journal of clinical pharmacology · 2010Review
- Novel opportunities for computational biology and sociology in drug discovery.Trends in biotechnology · 2010Review
- Novel opportunities for computational biology and sociology in drug discovery.Trends in biotechnology · 2009Review
- Determining molecular predictors of adverse drug reactions with causality analysis based on structure learning.Journal of the American Medical Informatics Association : JAMIAArticle
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 dangers of serious adverse drug reactions (SADRs) are well known to clinicians, pharmacologists, and the lay public. Efforts to elucidate the molecular mechanisms behind SADRs have made significant progress through genetics and gene expression measurements. However, as the field of pharmacology adopts the same novel higher-density measurement modalities that have proven successful in other areas of biology, one wonders whether there can be more ways to benefit from the explosion of data created by these tools. The development of analytic tools and algorithms to interpret these biological data to create tools for medicine is central to the field of translational bioinformatics. In this review we introduce some of the types of SADR predictors that are required, and we discuss several databases that are publicly available for the study of SADRs, ranging from clinical to molecular measurements. We also describe recent examples of how bioinformatics methods coupled with data repositories can advance the science of SADRs.
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.