Evidence map›Paper›PMID 16565883›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2006

Pharmacodynamic models for agents that alter production of natural cells with various distributions of lifespans.

Wojciech Krzyzanski, Sukyung Woo, William J Jusko

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.9field-weighted citation impact, top 10% 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

22 citing papers in PubMed, 40 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. The greatly misunderstood erythropoietin resistance index and the case for a new responsiveness measure.Hemodialysis international. International Symposium on Home Hemodialysis · 2016
    Article
  6. Models for the red blood cell lifespan.Journal of pharmacokinetics and pharmacodynamics · 2016
    Article
  7. Article
  8. Article
  9. Review
  10. Solution and implementation of distributed lifespan models.Journal of pharmacokinetics and pharmacodynamics · 2013
    Article
  11. Article
  12. Article
  13. Lifespan based indirect response models.Journal of pharmacokinetics and pharmacodynamics · 2012
    Review
  14. Article
  15. Article
  16. Article
  17. Simplification of an erythropoiesis model for design of anemia management protocols in end stage renal disease.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2011
    Article
  18. Erythropoietic response to endogenous erythropoietin in premature very low birth weight infants.The Journal of pharmacology and experimental therapeutics · 2010
    Article
  19. Article
  20. 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 1 institution in 1 country.

Wojciech KrzyzanskiDepartment of Pharmaceutical Sciences, State University of New York, Buffalo, New York 14260, USA. wk@buffalo.edu
Sukyung Woo
William J Jusko
University 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 GM 57980
6 · The paper itself

Abstract

Indirect pharmacodynamic response (IDR) models were developed for agents which alter the generation of cell populations with arbitrary lifespan distributions. These models extend lifespan based IDR models introduced previously [J. Pharmacokinet. Biopharm. 27: 467, 1999] for cell populations with the same lifespan ("delta" distribution). Considered are cell populations exhibiting time-invariant lifespan distributions described by the probability density function l(tau). It is assumed that cell response (R) is produced at a zero-order rate (kin(t)) and is eliminated from the population when the cell lifespan expires. The cell loss rate is calculated as kin*l(t), where '*' denotes the convolution operator. Therapeutic agents can stimulate or inhibit production rates according to the Hill function: 1 +/- H(C(t)) where H(C(t)) contains the capacity (Smax) and potency (SC50) parameters and C(t) is a pharmacokinetic function. The production rate is kin(t) = kin.[ 1+/-H(C(t))]. The operational model is dR/dt = kin(t)-kin*l(t) with the baseline condition R0 = kin.TR, where TR is the mean lifespan. Single populations as well as populations with precursors were examined by simulation to establish the role of lifespan distribution parameters (mean and standard deviation) in controlling the response vs. time profile. Estimability of parameters was assessed. Numerical techniques of solving differential equations with the convolution integral were proposed. In addition, the models were applied to literature data to describe the stimulatory effects of single doses of recombinant human erythropoietin on reticulocytes in blood. The estimates of Smax and SC50 for these agents were obtained along with means and standard deviations for reticulocyte lifespan distributions. The proposed models can be used to analyze the pharmacodynamics of agents which alter natural cell production yielding parameters describing their efficacy and potency as well as means and standard deviations for cell lifespan distributions.

Indexed as

Models, BiologicalAlgorithmsCell ProliferationCell SurvivalErythropoietinGrowth SubstancesHumansRecombinant ProteinsReticulocytesStatistical DistributionsStem CellsErythropoietinGrowth SubstancesRecombinant Proteins

Identifiers

PMID16565883
OpenAlexW2092216395

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.