ArticleJournal of pharmacokinetics and pharmacodynamics2005
A dynamical systems analysis of the indirect response model with special emphasis on time to peak response.
Article in Journal of pharmacokinetics and pharmacodynamics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Local application of engineered insulin-like growth factor I mRNA demonstrates regenerative therapeutic potentialMolecular therapy. Nucleic acids · 2023Article
- Modelling the delay between pharmacokinetics and EEG effects of morphine in rats: binding kinetic versus effect compartment models.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- Pattern Recognition in Pharmacodynamic Data Analysis.The AAPS journal · 2016Review
- Atazanavir-bilirubin interaction: a pharmacokinetic-pharmacodynamic model.Clinical pharmacology : advances and applications · 2013Article
- A flexible nonlinear feedback system that captures diverse patterns of adaptation and rebound.The AAPS journal · 2008Review
- Mathematical assessment of properties of precursor-dependent indirect pharmacodynamic response models.Journal of pharmacokinetics and pharmacodynamics · 2006Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper we present a mathematical analysis of the four classical indirect response models. We focus on characteristics such as the evolution of the response R(t) with time t, the time of maximal/minimal response T(max) and the area between the response and the baseline AUC(R), and the way these quantities depend on the drug dose, the dynamic parameters such as E(max) and EC50 and the ratio of the fractional turnover rate k(out) to the elimination rate constant k of drug in plasma. We find that depending on the model and on the drug mechanism function, T(max) may increase, decrease, decrease and then increase, or stay the same, as the drug dose is increased. This has important implications for using the shift in T(max) as a diagnostic tool in the selection of an appropriate model.
Indexed as
Identifiers
16307206What 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.