Evidence map›Paper›PMID 24025802›Full record

ReviewClinical pharmacology and therapeutics2013

Network-based approaches in drug discovery and early development.

J M Harrold, M Ramanathan, D E Mager

Open access · greenAbstract readReview
In one paragraph

Review in Clinical pharmacology and therapeutics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
12.0field-weighted citation impact, top 1% 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

52 citing papers in PubMed, 93 citations in OpenAlex.

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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.

J M HarroldDepartment of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
M Ramanathan
D E Mager
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 R01 GM057980PHS HHS 59780
6 · The paper itself

Abstract

Identification of novel targets is a critical first step in the drug discovery and development process. Most diseases such as cancer, metabolic disorders, and neurological disorders are complex, and their pathogenesis involves multiple genetic and environmental factors. Finding a viable drug target-drug combination with high potential for yielding clinical success within the efficacy-toxicity spectrum is extremely challenging. Many examples are now available in which network-based approaches show potential for the identification of novel targets and for the repositioning of established targets. The objective of this article is to highlight network approaches for identifying novel targets with greater chances of gaining approved drugs with maximal efficacy and minimal side effects. Further enhancement of these approaches may emerge from effectively integrating computational systems biology with pharmacodynamic systems analysis. Coupling genomics, proteomics, and metabolomics databases with systems pharmacology modeling may aid in the development of disease-specific networks that can be further used to build confidence in target identification.

Indexed as

Models, BiologicalSignal TransductionSystems BiologyAnimalsComputational BiologyDatabases, GeneticDrug DiscoveryGene Regulatory NetworksHumansMetabolic Networks and PathwaysMolecular Targeted TherapyPrecision Medicine

Identifiers

PMID24025802
PMCPMC4701200
OpenAlexW2000417339

What OpenQuestion holds

Textmetadata
LicenceTDM
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.