ReviewCPT: pharmacometrics & systems pharmacology2018
Translational Biomedical Informatics and Pharmacometrics Approaches in the Drug Interactions Research.
Review in CPT: pharmacometrics & systems pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Mol2Image: an enhanced DDI prediction framework leveraging drug molecular descriptors.BMC bioinformatics · 2026Article
- A Dose-Aware Model for Revealing Dose-Risk Relationship of Drug-Drug Interaction.CPT: pharmacometrics & systems pharmacology · 2025Article
- PS3N: leveraging protein sequence-structure similarity for novel drug-drug interaction discovery.Scientific reports · 2025Article
- Deep learning-enabled natural language processing to identify directional pharmacokinetic drug-drug interactions.BMC bioinformatics · 2023Article
- Predicting the Effect of Renal Function on Systemic Clearance: Is a Simple Scaling Method Sufficient?Journal of pharmaceutical sciences · 2023Article
- MSEDDI: Multi-Scale Embedding for Predicting Drug-Drug Interaction Events.International journal of molecular sciences · 2023Article
- Peripheral Neuropathy During Concomitant Administration of Proteasome Inhibitors and Factor Xa Inhibitors: Identifying the Likelihood of Drug-Drug Interactions.Frontiers in pharmacology · 2022Article
- Mining Social Media Data for Biomedical Signals and Health-Related Behavior.Annual review of biomedical data science · 2020Article
- Mining and visualizing high-order directional drug interaction effects using the FAERS database.BMC medical informatics and decision making · 2020Article
- Opportunities and Challenges of Using Big Data to Detect Drug-Drug Interaction Risk.Clinical pharmacology and therapeutics · 2019Article
- Reverse Translational Pharmacology Research Is Driven by Big Data.CPT: pharmacometrics & systems pharmacology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Drug interaction is a leading cause of adverse drug events and a major obstacle for current clinical practice. Pharmacovigilance data mining, pharmacokinetic modeling, and text mining are computation and informatic tools on integrating drug interaction knowledge and generating drug interaction hypothesis. We provide a comprehensive overview of these translational biomedical informatics methodologies with related databases. We hope this review illustrates the complementary nature of these informatic approaches and facilitates the translational drug interaction research.
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.