Evidence map›Paper›PMID 26935745›Full record

ArticleMalaria journal2016

Analysis of ex vivo drug response data of Plasmodium clinical isolates: the pros and cons of different computer programs and online platforms.

Grennady Wirjanata, Irene Handayuni, Sophie G Zaloumis, Ferryanto Chalfein, Pak Prayoga, Enny Kenangalem, Jeanne Rini Poespoprodjo, Rintis Noviyanti, Julie A Simpson, Ric N Price and 1 more

Abstract read
In one paragraph

Article in Malaria journal, 2016. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

11 authors.

Grennady WirjanataGlobal and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, PO Box 41096, Casuarina, Darwin, NT, 0811, Australia. Grennady.Wirjanata@menzies.edu.au.
Irene HandayuniGlobal and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, PO Box 41096, Casuarina, Darwin, NT, 0811, Australia. Irene.Handayuni@menzies.edu.au.
Sophie G ZaloumisCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia. sophiez@unimelb.edu.au.
Ferryanto ChalfeinPapuan Health and Community Development Foundation (PHCDF), Timika, Papua, Indonesia. ferryanto_cs@yahoo.com.
Pak PrayogaPapuan Health and Community Development Foundation (PHCDF), Timika, Papua, Indonesia. prayogatimika@gmail.com.
Enny KenangalemPapuan Health and Community Development Foundation (PHCDF), Timika, Papua, Indonesia. ennykenangalem@yahoo.com.
Jeanne Rini PoespoprodjoPapuan Health and Community Development Foundation (PHCDF), Timika, Papua, Indonesia. didot2266@yahoo.com.
Rintis NoviyantiEijkman Institute for Molecular Biology, Jl. Diponegoro 69, 10430, Jakarta, Indonesia. rintis@eijkman.go.id.
Julie A SimpsonCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia. julieas@unimelb.edu.au.
Ric N PriceGlobal and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, PO Box 41096, Casuarina, Darwin, NT, 0811, Australia. ricprice99@googlemail.com.
Jutta MarfurtGlobal and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, PO Box 41096, Casuarina, Darwin, NT, 0811, Australia. jutta.marfurt@menzies.edu.au.

Funding

Wellcome Trust 091625
6 · The paper itself

Abstract

backgroundIn vitro drug susceptibility testing of malaria parasites remains an important component of surveillance for anti-malarial drug resistance. The half-maximal inhibition of growth (IC50) is the most commonly reported parameter expressing drug susceptibility, derived by a variety of statistical approaches, each with its own advantages and disadvantages.

methodsIn this study, licensed computer programs WinNonlin and GraphPad Prism 6.0, and the open access programs HN-NonLin, Antimalarial ICEstimator (ICE), and In Vitro Analysis and Reporting Tool (IVART) were tested for their ease of use and ability to estimate reliable IC50 values from raw drug response data from 31 Plasmodium falciparum and 29 P. vivax clinical isolates tested with five anti-malarial agents: chloroquine, amodiaquine, piperaquine, mefloquine, and artesunate.

resultsThe IC50 and slope estimates were similar across all statistical packages for all drugs tested in both species. There was good correlation of results derived from alternative statistical programs and non-linear mixed-effects modelling (NONMEM) which models all isolate data simultaneously. The user-friendliness varied between packages. While HN-NonLin and IVART allow users to enter the data in 96-well format, IVART and GraphPad Prism 6.0 are capable to analyse multiple isolates and drugs in parallel. WinNonlin, GraphPad Prism 6.0, IVART, and ICE provide alerts for non-fitting data and incorrect data entry, facilitating data interpretation. Data analysis using WinNonlin or ICE took the longest computationally, whilst the offline ability of GraphPad Prism 6.0 to analyse multiple isolates and drugs simultaneously made it the fastest among the programs tested.

conclusionIC50 estimates obtained from the programs tested were comparable. In view of processing time and ease of analysis, GraphPad Prism 6.0 or IVART are best suited for routine and large-scale drug susceptibility testing.

Indexed as

Computer SimulationSoftwareAntimalarialsComputational BiologyDrug ResistanceHumansInhibitory Concentration 50InternetMalaria, FalciparumMalaria, VivaxParasitic Sensitivity TestsPlasmodium falciparumPlasmodium vivaxAntimalarials

Identifiers

PMID26935745
PMCPMC4776429

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LicenceCC BY
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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.