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Cited by 214

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Optimizing Combination Chemotherapy by Controlling Drug Ratios

Mayer, L. D., Janoff, A. S.·2007·Molecular Interventions

Abstract

Cancer chemotherapy treatments typically employ drug combinations in which the dose of each agent is pushed to the brink of unacceptable toxicity; however, emerging evidence indicates that this approach may not be providing optimal efficacy due to the manner in which drugs interact. Specifically, whereas certain ratios of combined drugs can be synergistic, other ratios of the same agents may be antagonistic, implying that the most efficacious combinations may be those that utilize certain agents at reduced doses. Advances in nano-scale drug delivery vehicles now enable the translation of in vitro information on synergistic drug ratios into improved anticancer combination therapies in which the desired drug ratio can be controlled and maintained following administration in vivo, so that synergistic effects can be exploited. This "ratiometric" approach to combination chemotherapy opens new opportunities to enhance the effectiveness of existing and future treatment regimens across a spectrum of human diseases.

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Metadata

Authors
Mayer, L. D., & Janoff, A. S.
Venue
Molecular Interventions
Published
2007-08-01
Volume
7
Issue
4
Pages
216-223
ISSN
1534-0384 (ISSN-L)
OpenAlex
W1989789824
Cited by
214
References
2
FWCI
3.53
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Optimizing Combination Chemotherapy by Controlling Drug Ratios. https://app.cochat.ai/papers/10.1124/mi.7.4.8
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Mayer, L. D., & Janoff, A. S. (2007). Optimizing Combination Chemotherapy by Controlling Drug Ratios. Molecular Interventions. https://doi.org/10.1124/mi.7.4.8

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.