ArticlePloS one2018
Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits.
Article in PloS one, 2018. 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, 25 citations in OpenAlex.
- Physiologically based pharmacokinetic models for systemic disposition of protein therapeutics in rabbits.Frontiers in pharmacology · 2024Article
- Quantitative systems pharmacology of the eye: Tools and data for ocular QSP.CPT: pharmacometrics & systems pharmacology · 2023Review
- Application of machine learning in combination with mechanistic modeling to predict plasma exposure of small molecules.Frontiers in systems biology · 2023Article
- A multi-model approach to predict efficacious clinical dose for an anti-TGF-β antibody (GC2008) in the treatment of osteogenesis imperfecta.CPT: pharmacometrics & systems pharmacology · 2022Article
- Streamlining physiologically-based pharmacokinetic model design for intravenous delivery of nanoparticle drugs.CPT: pharmacometrics & systems pharmacology · 2022Article
- Quantitative Comparison of Avian and Mammalian Physiologies for Parameterization of Physiologically Based Kinetic Models.Frontiers in physiology · 2022Article
- A workflow to build PBTK models for novel species.Archives of toxicology · 2020Article
- Predictive modeling of aspirin-triggered resolvin D1 pharmacokinetics for the study of Sjögren's syndrome.Clinical and experimental dental research · 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
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The environmental fates of pharmaceuticals and the effects of crop protection products on non-target species are subjects that are undergoing intense review. Since measuring the concentrations and effects of xenobiotics on all affected species under all conceivable scenarios is not feasible, standard laboratory animals such as rabbits are tested, and the observed adverse effects are translated to focal species for environmental risk assessments. In that respect, mathematical modelling is becoming increasingly important for evaluating the consequences of pesticides in untested scenarios. In particular, physiologically based pharmacokinetic/toxicokinetic (PBPK/TK) modelling is a well-established methodology used to predict tissue concentrations based on the absorption, distribution, metabolism and excretion of drugs and toxicants. In the present work, a rabbit PBPK/TK model is developed and evaluated with data available from the literature. The model predictions include scenarios of both intravenous (i.v.) and oral (p.o.) administration of small and large compounds. The presented rabbit PBPK/TK model predicts the pharmacokinetics (Cmax, AUC) of the tested compounds with an average 1.7-fold error. This result indicates a good predictive capacity of the model, which enables its use for risk assessment modelling and simulations.
Indexed as
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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.