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Cited by 720

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

A Method for Testing for Synergy with Any Number of Agents

Berenbaum, M. C.·1978·Journal of Infectious Diseases

Abstract

The standard checkerboard titration for detecting synergy between antibiotics is practicable for combinations of two antibiotics, laborious for combinations of three, and not feasible for combinations of four or more. Nevertheless, methods for testing of combinations of several antibiotics are urgently needed because some combinations might be superior to those in use and enable the successful treatment of infections resistant to current therapy. A simple method for measurement of synergy (or antagonism) with combinations of any number of agents has been developed which requires less effort than the standard checkerboard titration of two agents. With this method, the concentrations of each of n agents producing some specified effect (such as minimal inhibitory concentration or minimal bactericidal concentration) are determined. A reference combination made up of 1/n of each of these concentrations is titrated to find a dilution that produces the specified effect. The degree of dilution required is equal to the sum of the fractional inhibitory concentrations (concentration of each agent in combination/concentration of each agent alone) as conventionally determined by checkerboard titrations; sums of less than 1, 1, and greater than 1 indicate synergy, additivity, and antagonism, respectively.

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Metadata

Authors
Berenbaum, M. C.
Venue
Journal of Infectious Diseases
Published
1978-02-01
Volume
137
Issue
2
Pages
122-130
ISSN
  • 0022-1899 (ISSN-L)
  • 1537-6613
OpenAlex
W2112191861
Cited by
720
References
8
FWCI
8.23
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Method for Testing for Synergy with Any Number of Agents. https://app.cochat.ai/papers/10.1093/infdis/137.2.122
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Berenbaum, M. C. (1978). A Method for Testing for Synergy with Any Number of Agents. Journal of Infectious Diseases. https://doi.org/10.1093/infdis/137.2.122

Data sources

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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.