Evidence map›Paper›PMID 25416501›Full record

ReviewExpert opinion on drug metabolism & toxicology2015

Animal models for exploring the pharmacokinetics of breast cancer therapies.

Omar M Rashid, Kazuaki Takabe

Abstract readReview
In one paragraph

Review in Expert opinion on drug metabolism & toxicology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Biological profile of breast cancer brain metastasis.Acta neuropathologica communications · 2025
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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

2 authors.

Omar M RashidH. Lee Moffitt Cancer Center and Research Institute , Tampa, FL , USA.
Kazuaki Takabe

Funding

Sphingosine-1 Phosphate in Breast Cancer Progression and LymphangiogenesisR01CA160688 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI TAKABE, KAZUAKI · 2012 to 2016
$1.5M
NCI NIH HHS R01 CA160688NCI NIH HHS R01CA160688
6 · The paper itself

Abstract

introductionDespite massive expenditures in research and development to cure breast cancer, few agents that pass preclinical trials demonstrate efficacy in humans. Although this endeavor relies on murine models to screen for efficacy before progressing to clinical trials, historically there has been little focus on the validation of these models, even in the era of targeted therapy where understanding the genetic signatures of tumors under study is critical. AREAS COVERED: This review includes the transgenic, xenograft, and syngeneic murine breast cancer models, the ectopic, orthotopic and intravenous methods of cell implantation, and the ethics of animal experimentation. It also includes the latest data on tumor gene expression and the issues to consider when exploring the pharmacokinetics and efficacy of breast cancer therapies. EXPERT OPINION: Breast cancer drug development is expensive and inefficient without a consensus preclinical murine model. Investigators must approach the choice of murine model with the same sophistication that is applied to the choice of in vitro assays to improve efficiency. Understanding the limitations of each model available, including the nuances of tumor gene signatures, is critical for investigators exploring the phamacokinetics and efficacy of breast cancer therapies, especially in the context of gene profiling and individualized targeted therapy.

Indexed as

Disease Models, AnimalAnimalsAntineoplastic AgentsBreast NeoplasmsDrug DesignFemaleGene Expression Regulation, NeoplasticHumansMiceMice, TransgenicXenograft Model Antitumor AssaysAntineoplastic Agentsbreast cancer drug developmentmurine metastatic model

Identifiers

PMID25416501
PMCPMC4583421

What OpenQuestion holds

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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.