The mighty mouse: Genetically engineered mouse models in cancer drug development
Nature Reviews Drug Discovery, ISSN: 1474-1776, Vol: 5, Issue: 9, Page: 741-754
2006
- 547Citations
- 492Captures
- 3Mentions
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations547
- Citation Indexes543
- 543
- CrossRef490
- Policy Citations3
- Policy Citation3
- Clinical Citations1
- PubMed Guidelines1
- Captures492
- Readers492
- 492
- Mentions3
- References3
- Wikipedia3
Review Description
Deficiencies in the standard preclinical methods for evaluating potential anticancer drugs, such as xenograft mouse models, have been highlighted as a key obstacle in the translation of the major advances in basic cancer research into meaningful clinical benefits. In this article, we discuss the established uses and limitations of xenograft mouse models for cancer drug development, and then describe the opportunities and challenges in the application of novel genetically engineered mouse models that more faithfully mimic the genetic and biological evolution of human cancers. Greater use of such models in target validation, assessment of tumour response, investigation of pharmacodynamic markers of drug action, modelling resistance and understanding toxicity has the potential to markedly improve the success of cancer drug development.
Bibliographic Details
Springer Science and Business Media LLC
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