Evidence map›Paper›PMID 30617672›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2019

Ordinary differential equation approximation of gamma distributed delay model.

Wojciech Krzyzanski

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Delay differential equations based models in NONMEM.Journal of pharmacokinetics and pharmacodynamics · 2021
    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 at 1 institution in 1 country.

Wojciech KrzyzanskiDepartment of Pharmaceutical Sciences, University at Buffalo, 370 Kapoor Hall, Buffalo, NY, 14214, USA. wk@buffalo.edu.ORCID http://orcid.org/0000-0001-9773-1739
University at Buffalo, State University of New York · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In many models of pharmacodynamic systems with delays, a delay of an input is introduced by means of the convolution with the gamma distribution. An approximation of the convolution integral of bound functions based on a system of ordinary differential equations that utilizes properties of the binomial series has been introduced. The approximation converges uniformly on every compact time interval and an estimate of the approximation error has been found [Formula: see text] where [Formula: see text] is the number of differential equations and [Formula: see text] is the shape parameter of the gamma distribution. The accuracy of approximation has been tested on a set of input functions for which the convolution is known explicitly. For tested functions, [Formula: see text] has resulted in an accurate approximation, if [Formula: see text]. However, if [Formula: see text] the error of approximation decreases slowly with increasing [Formula: see text], and [Formula: see text] might be necessary to achieve acceptable accuracy. Finally, the approximation was applied to estimate parameters for the distributed delay model of chemotherapy-induced myelosuppression from previously published WBC count data in rats treated with 5-fluorouracil.

Indexed as

Models, BiologicalAlgorithmsAnimalsFluorouracilGranulocyte Precursor CellsHumansRatsFluorouracilBinomial seriesChemotherapy-induced myelosuppressionConvolutionGamma distributionPharmacodynamicsTransit compartments model

Identifiers

PMID30617672
OpenAlexW2909373455

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.