Evidence map›Paper›PMID 26377617›Full record

ReviewJournal of pharmacokinetics and pharmacodynamics2015

Pharmacodynamic models of age-structured cell populations.

Wojciech Krzyzanski

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of pharmacokinetics and pharmacodynamics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Special issue: mathematical pharmacology.Journal of pharmacokinetics and pharmacodynamics · 2018
    Article
  3. Age-structured population model of cell survival.Journal of pharmacokinetics and pharmacodynamics · 2017
    Article
  4. Perspectives on the history and scientific contributions of Gerhard Levy.Journal of pharmacokinetics and pharmacodynamics · 2015
    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

1 author.

Wojciech KrzyzanskiDepartment of Pharmaceutical Sciences, University at Buffalo, 370 Kapoor Hall, Buffalo, NY, 14214, USA. wk@buffalo.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this work is to review basic pharmacodynamic (PD) models describing drug effects on cell populations and expand them to age-structured models using the theory of physiologically structured populations. The plasma drug concentrations are interpreted as the environment affecting the cell production and mortality rates. An explicit solution to model equations provides the age density distribution that serves to establish a relationship between the cell lifespan distribution and the hazard of cell removal. Given the lifespan distributions, the age distributions for most commonly applied PD models of cell responses including basic cell turnover, transit compartments, and basic lifespan models have been derived both for the baseline conditions and drug treatment. The steady-state age distribution for basic indirect response models is exponential, and it is uniform for the basic lifespan model. As an example of more complex cell population, the age distribution of human red blood cells has been simulated based on a recent model of red blood cell survival. The age distribution for cells in the transit compartment model is the sum of the gamma functions. Means and variances of age distributions for all discussed models were calculated. A brief discussion of numerical challenges and possible future model developments is presented.

Indexed as

Models, BiologicalAlgorithmsCell SurvivalComputer SimulationErythrocytesHumansModels, StatisticalPharmaceutical PreparationsPharmaceutical PreparationsAge structureCell populationLifespan distributionMortality ratePharmacodynamic model

Identifiers

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.