ArticlePLoS computational biology2018
PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development.
Article in PLoS computational biology, 2018. 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
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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, 19 citations in OpenAlex.
- Curated and Structure-Based Drug-Target Interactions Improve Underprediction of Drug Side Effects in Network Models.Journal of chemical information and modeling · 2026Article
- Uncovering New Therapeutic Targets for Amyotrophic Lateral Sclerosis and Neurological Diseases Using Real-World Data.Clinical pharmacology and therapeutics · 2025Article
- Across preclinical and clinical platforms, approved and investigational psychiatric drugs share pathways and associate with similar molecular functions.Frontiers in drug discovery · 2025Article
- Preclinical side effect prediction through pathway engineering of protein interaction network models.CPT: pharmacometrics & systems pharmacology · 2024Article
- Beta-2 adrenergic receptor agonism alters astrocyte phagocytic activity and has potential applications to psychiatric disease.Discover mental health · 2023Article
- Drug target, class level, and PathFX pathway information share utility for machine learning prediction of common drug-induced side effects.Frontiers in drug safety and regulation · 2023Article
- A network paradigm predicts drug synergistic effects using downstream protein-protein interactions.CPT: pharmacometrics & systems pharmacology · 2022Article
- Advancing drug safety science by integrating molecular knowledge with post-marketing adverse event reports.CPT: pharmacometrics & systems pharmacology · 2022Review
- From random to predictive: a context-specific interaction framework improves selection of drug protein-protein interactions for unknown drug pathways.Integrative biology : quantitative biosciences from nano to macro · 2022Article
- Article
- Leveraging Human Genetics to Identify Safety Signals Prior to Drug Marketing Approval and Clinical Use.Drug safety · 2020Article
- PathFXweb: a web application for identifying drug safety and efficacy phenotypes.Bioinformatics (Oxford, England) · 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
8 authors at 2 institutions in 1 country.
Funding
Abstract
Failure to demonstrate efficacy and safety issues are important reasons that drugs do not reach the market. An incomplete understanding of how drugs exert their effects hinders regulatory and pharmaceutical industry projections of a drug's benefits and risks. Signaling pathways mediate drug response and while many signaling molecules have been characterized for their contribution to disease or their role in drug side effects, our knowledge of these pathways is incomplete. To better understand all signaling molecules involved in drug response and the phenotype associations of these molecules, we created a novel method, PathFX, a non-commercial entity, to identify these pathways and drug-related phenotypes. We benchmarked PathFX by identifying drugs' marketed disease indications and reported a sensitivity of 41%, a 2.7-fold improvement over similar approaches. We then used PathFX to strengthen signals for drug-adverse event pairs occurring in the FDA Adverse Event Reporting System (FAERS) and also identified opportunities for drug repurposing for new diseases based on interaction paths that associated a marketed drug to that disease. By discovering molecular interaction pathways, PathFX improved our understanding of drug associations to safety and efficacy phenotypes. The algorithm may provide a new means to improve regulatory and therapeutic development decisions.
Indexed as
Identifiers
What Socratic 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 Socratic graph.