Interaction Index and Different Methods for Determining Drug Interaction in Combination Therapy
Abstract
Studying and understanding the joint effect of combined treatments is important in pharmacology and in the development of combination therapies. The Loewe additivity model is one of the best general reference models for evaluating drug interactions. Based on this model, synergy occurs when the interaction index is less than one, while antagonism occurs when interaction index is greater than one. We expanded the meaning of the interaction index, and propose a procedure to calculate the interaction index and its associated confidence interval under the assumption that the dose-effect curve for a single agent follows Chou and Talalay's median effect equation. In addition, we review four response surface models based on the Loewe additivity model using a single parameter to determine drug interactions. We describe each of these models in the context of Loewe additivity model and discuss their relative advantages and disadvantages. We also provide S-PLUS/R code for each approach to facilitate the implementation of these commonly used methods.
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The one-stage modeling failed to converge when analyzing the data from Lee et al. (2007).
“The one-stage modeling failed to converge when we analyzed the data from Lee et al (2007) (Table 4).”
From Evaluation of Drug Combination Effect Using a Bliss Independence Dose–Response Surface Model (2018) · cites this paper as Lee et al (2007)
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Chou, T.-C., & Talalay, P. (1984) · Advances in Enzyme Regulation · doi:10.1016/0065-2571(84)90007-4 · Cited by 7,178 · see citing works
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Searching for Drug Synergy in Complex Dose–Response Landscapes Using an Interaction Potency Model
Yadav, B., Wennerberg, K., Aittokallio, T., & Tang, J. (2015) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2015.09.001 · Cited by 845 · see citing works
Evaluation of Drug Combination Effect Using a Bliss Independence Dose–Response Surface Model
Liu, Q., Yin, X., Languino, L. R., & Altieri, D. C. (2018) · Statistics in Biopharmaceutical Research · doi:10.1080/19466315.2018.1437071 · Cited by 216 · see citing works
Saw, C. L.-L., Cintrón, M., Wu, T.-Y., Guo, Y., Huang, Y., Jeong, W.-S., & Kong, A.-N. T. (2011) · Biopharmaceutics & Drug Disposition · doi:10.1002/bdd.759 · Cited by 118 · see citing works
Yan, H., Zhang, B., Li, S., & Zhao, Q. (2010) · BMC Systems Biology · doi:10.1186/1752-0509-4-50 · Cited by 73 · see citing works
- Authors
- Lee, J. J., Kong, M., Ayers, G. D., & Lotan, R.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- University of Louisville (US)
- Vanderbilt University Medical Center (US)
- Corresponding author
- Lee, J. J.
- ORCID
- Kong, M.
- Venue
- Journal of Biopharmaceutical Statistics
- Publisher
- Informa UK Limited
- Published
- 2007-05-01
- Volume
- 17
- Issue
- 3
- Pages
- 461-480
- ISSN
- 1054-3406 (ISSN-L)
- 1520-5711
- OpenAlex
- W2151672555
- Cited by
- 135
- References
- 1
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 3 · 2023: 6 · 2022: 9 · 2021: 4 · 2020: 7 · 2019: 7 · 2018: 6 · 2017: 11 · 2016: 9 · 2015: 14 · 2014: 10 · 2013: 6 · 2012: 8
- FWCI
- 6.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Biopharmaceutical Statistics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (CA-16672, P50CA097007, P01CA091844, CA 91844, CA97007., P30CA016672)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- drug interactions, interaction index, combination therapy, synergistic effect, antagonism, response surface model, confidence intervals, dose-response curves
- MeSH terms
- Animals, Antineoplastic Agents, Cell Survival, Data Interpretation, Statistical, Dose-Response Relationship, Drug, Drug Antagonism, Drug Interactions, Drug Synergism, Drug Therapy, Combination, Humans, Models, Biological, Reproducibility of Results, Models, Statistical, Confidence Intervals, Cell Line, Tumor
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