Evidence map›Paper›PMID 27727128›Full record

ReviewTrends in parasitology2017

Mathematical Modelling to Guide Drug Development for Malaria Elimination.

Hannah C Slater, Lucy C Okell, Azra C Ghani

Abstract readReview
In one paragraph

Review in Trends in parasitology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
–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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  15. An ecosystem framework for understanding and treating disease.Evolution, medicine, and public health · 2018
    Review
  16. Reply to Rossi et al.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2017
    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.

Hannah C SlaterMRC Centre for Outbreak Analysis & Modelling, Department of Infectious Disease Epidemiology, Imperial College London, UK.
Lucy C OkellMRC Centre for Outbreak Analysis & Modelling, Department of Infectious Disease Epidemiology, Imperial College London, UK.
Azra C GhaniMRC Centre for Outbreak Analysis & Modelling, Department of Infectious Disease Epidemiology, Imperial College London, UK. Electronic address: a.ghani@imperial.ac.uk.

Funding

Medical Research Council G1002387Medical Research Council MR/K010174/1
6 · The paper itself

Abstract

Mathematical models of the dynamics of a drug within the host are now frequently used to guide drug development. These generally focus on assessing the efficacy and duration of response to guide patient therapy. Increasingly, antimalarial drugs are used at the population level, to clear infections, provide chemoprevention, and to reduce onward transmission of infection. However, there is less clarity on the extent to which different drug properties are important for these different uses. In addition, the emergence of drug resistance poses new threats to longer-term use and highlights the need for rational drug development. Here, we argue that integrating within-host pharmacokinetic and pharmacodynamic (PK/PD) models with mathematical models for the population-level transmission of malaria is key to guiding optimal drug design to aid malaria elimination.

Indexed as

Disease EradicationModels, TheoreticalAntimalarialsDrug DesignDrug ResistanceHumansMalaria, FalciparumPlasmodium falciparumAntimalarialsdrug-based strategiesdrug developmentmalariamathematical modellingPlasmodium falciparumPlasmodium vivax

Identifiers

PMID27727128
PMCPMC5347022

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.