ReviewCPT: pharmacometrics & systems pharmacology2022
Advancing drug safety science by integrating molecular knowledge with post-marketing adverse event reports.
Review in CPT: pharmacometrics & systems pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Strengthening Signal Detection in Pharmacovigilance by Using International Nonproprietary Name (INN) Stems.Drug safety · 2026Review
- A review on adverse drug reaction related to medication in health sector: an account of what we have discovered and implemented-pharmacovigilance.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- A brief reference to AI-driven audible reality (AuRa) in open world: potential, applications, and evaluation.Frontiers in artificial intelligence · 2024Article
- Modeling tumor size dynamics based on real-world electronic health records and image data in advanced melanoma patients receiving immunotherapy.CPT: pharmacometrics & systems pharmacology · 2023Article
- Application of an Integrative Drug Safety Model for Detection of Adverse Drug Events Associated With Inhibition of Glutathione Peroxidase 1 in Chronic Obstructive Pulmonary Disease.Pharmaceutical research · 2023Article
- Conducting and interpreting disproportionality analyses derived from spontaneous reporting systems.Frontiers in drug safety and regulation · 2023Review
- Quantitative approaches to drug safety: The 2022 PSP special issue.CPT: pharmacometrics & systems pharmacology · 2022Article
- Advancing drug safety science by integrating molecular knowledge with post-marketing adverse event reports.CPT: pharmacometrics & systems pharmacology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Promising drug development efforts may frequently fail due to unintended adverse reactions. Several methods have been developed to analyze such data, aiming to improve pharmacovigilance and drug safety. In this work, we provide a brief review of key directions to quantitatively analyzing adverse events and explore the potential of augmenting these methods using additional molecular data descriptors. We argue that molecular expansion of adverse event data may provide a path to improving the insights gained through more traditional pharmacovigilance approaches. Examples include the ability to assess statistical relevance with respect to underlying biomolecular mechanisms, the ability to generate plausible causative hypotheses and/or confirmation where possible, the ability to computationally study potential clinical trial designs and/or results, as well as the further provision of advanced features incorporated in innovative methods, such as machine learning. In summary, molecular data expansion provides an elegant way to extend mechanistic modeling, systems pharmacology, and patient-centered approaches for the assessment of drug safety. We anticipate that such advances in real-world data informatics and outcome analytics will help to better inform public health, via the improved ability to prospectively understand and predict various types of drug-induced molecular perturbations and adverse events.
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.