ArticleClinical pharmacology and therapeutics2018
The Influence of Big (Clinical) Data and Genomics on Precision Medicine and Drug Development.
Article in Clinical pharmacology and therapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 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
33 citing papers in PubMed.
- From In Silico Hypothesis to Validation: The Role of Real-World Evidence in the Preliminary Verification of AI-Generated Drug-Repositioning Candidates: A Comprehensive Review.Journal of clinical medicine · 2026Review
- Unveiling non-small cell lung cancer treatment effect heterogeneity: a comparative analysis of statistical methods.Journal of the National Cancer Institute · 2025Article
- Advances and challenges in drug repurposing in precision therapeutics of colorectal cancer.World journal of gastrointestinal oncology · 2025Review
- Systematic method for classifying multiple congenital anomaly cases in electronic health records.Genetics in medicine : official journal of the American College of Medical Genetics · 2025Article
- The Potential of Artificial Intelligence in Pharmaceutical Innovation: From Drug Discovery to Clinical Trials.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Big data for neuroscience in the context of predictive, preventive, and personalized medicine.The EPMA journal · 2025Review
- Comparing genomic studies in animal breeding and human genetics: focus on disease-related traits in livestock - A review.Animal bioscience · 2025Article
- Overcoming challenges associated with broad sharing of human genomic data.Nature genetics · 2025Review
- Exploring the ethical issues posed by AI and big data technologies in drug development.Frontiers in public health · 2025Review
- Preclinical murine models for the testing of antimicrobials against Mycobacterium abscessus pulmonary infections: Current practices and recommendations.Tuberculosis (Edinburgh, Scotland) · 2024Review
- DRAGON-Data: a platform and protocol for integrating genomic and phenotypic data across large psychiatric cohorts.BJPsych open · 2023Article
- BETA: a comprehensive benchmark for computational drug-target prediction.Briefings in bioinformatics · 2022Article
- The Built Environment Assessment of Residential Areas in Wuhan during the Coronavirus Disease (COVID-19) Outbreak.International journal of environmental research and public health · 2022Article
- Computational drug repurposing based on electronic health records: a scoping review.NPJ digital medicine · 2022Article
- From pharmacogenetics to pharmaco-omics: Milestones and future directions.HGG advances · 2022Review
- Cox regression is robust to inaccurate EHR-extracted event time: an application to EHR-based GWAS.Bioinformatics (Oxford, England) · 2022Article
- Evaluating the performance of drug-repurposing technologies.Drug discovery today · 2022Review
- The Interface of Therapeutics and Genomics in Cardiovascular Medicine.Cardiovascular drugs and therapy · 2021Review
- Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing.Medicinal research reviews · 2020Review
- Precision cardiovascular medicine in China.Journal of geriatric cardiology : JGC · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Drug development continues to be costly and slow, with medications failing due to lack of efficacy or presence of toxicity. The promise of pharmacogenomic discovery includes tailoring therapeutics based on an individual's genetic makeup, rational drug development, and repurposing medications. Rapid growth of large research cohorts, linked to electronic health record (EHR) data, fuels discovery of new genetic variants predicting drug action, supports Mendelian randomization experiments to show drug efficacy, and suggests new indications for existing medications. New biomedical informatics and machine-learning approaches advance the ability to interpret clinical information, enabling identification of complex phenotypes and subpopulations of patients. We review the recent history of use of "big data" from EHR-based cohorts and biobanks supporting these activities. Future studies using EHR data, other information sources, and new methods will promote a foundation for discovery to more rapidly advance precision medicine.
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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.