Evidence map›Paper›PMID 18551354›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2008

Basic pharmacodynamic models for agents that alter the lifespan distribution of natural cells.

Wojciech Krzyzanski, Juan Jose Perez-Ruixo, An Vermeulen

Open access · bronzeAbstract read
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.5field-weighted citation impact, top 12% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 30 citations in OpenAlex.

  1. Trial
  2. Delay differential equations based models in NONMEM.Journal of pharmacokinetics and pharmacodynamics · 2021
    Article
  3. Ordinary differential equation approximation of gamma distributed delay model.Journal of pharmacokinetics and pharmacodynamics · 2019
    Article
  4. Article
  5. Models for the red blood cell lifespan.Journal of pharmacokinetics and pharmacodynamics · 2016
    Article
  6. Pharmacodynamic models of age-structured cell populations.Journal of pharmacokinetics and pharmacodynamics · 2015
    Review
  7. Mathematical model of platelet turnover in thrombocytopenic and nonthrombocytopenic preterm neonates.American journal of physiology. Heart and circulatory physiology · 2015
    Article
  8. Article
  9. Article
  10. Article
  11. Lifespan based indirect response models.Journal of pharmacokinetics and pharmacodynamics · 2012
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 3 countries.

Wojciech KrzyzanskiDepartment of Pharmaceutical Sciences, University at Buffalo, Buffalo, NY 14260, USA. wk@buffalo.edu
Juan Jose Perez-Ruixo
An Vermeulen
Johnson & Johnson (Brazil) · BRUniversitat de Miguel Hernández d'Elx · ESUniversity at Buffalo, State University of New York · US

Funding

MATHEMATICAL MODELS IN PHARMACODYNAMICSR01GM057980 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI JUSKO, WILLIAM J., KRZYZANSKI, WOJCIECH · 1998 to 2013
$3.4M
NIGMS NIH HHS R01 GM057980
6 · The paper itself

Abstract

A new class of basic indirect pharmacodynamic models for agents that alter the loss of natural cells based on a lifespan concept are presented. The lifespan indirect response (LIDR) models assume that cells (R) are produced at a constant rate (k(in)), survive during a certain duration T(R), and finally are lost. The rate of cell loss is equal to the production rate but is delayed by T(R). A therapeutic agent can increase or decrease the baseline cell lifespan to a new cell lifespan, T(D), by temporally changing the proportion of cells belonging to the two modes of the lifespan distribution. Therefore, the change of lifespan at time t is described according to the Hill function, H(C(t)), with capacity (E(max)) and sensitivity (EC(50)), and the pharmacokinetic function C(t). A one-compartment cell model was examined through simulations to describe the role of pharmacokinetics, pharmacodynamics and cell properties for the cases where the drug increases (T(D) > T(R)) or decreases (T(D) < T(R)) the cell lifespan. The area under the effect curve (AUCE) and explicit solutions of LIDR models for large doses were derived. The applicability of the model was further illustrated using the effects of recombinant human erythropoietin (rHuEPO) on reticulocytes. The cases of both stimulation of the proliferation of bone marrow progenitor cells and the increase of reticulocyte lifespans were used to describe mean data from healthy subjects who received single subcutaneous doses of rHuEPO ranging from 20 to 160 kIU. rHuEPO is about 4.5-fold less potent in increasing reticulocyte survival than in stimulating the precursor production. A maximum increase of 4.1 days in the mean reticulocyte lifespan was estimated and the effect duration on the lifespan distribution was dose dependent. LIDR models share similar properties with basic indirect response models describing drug stimulation or inhibition of the response loss rate with the exception of the presence of a lag time and a dose independent peak time. The current concept can be applied to describe the pharmacodynamic effects of agents affecting survival of hematopoietic cell populations yielding realistic physiological parameters.

Indexed as

PharmacokineticsArea Under CurveBone Marrow CellsCell CountCell ProliferationCell SurvivalDose-Response Relationship, DrugErythroid Precursor CellsErythropoietinHumansInjections, SubcutaneousModels, StatisticalRecombinant ProteinsReticulocytesErythropoietinRecombinant Proteins

Identifiers

PMID18551354
PMCPMC2673548
OpenAlexW2059824590

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.