Analysis of drug combinations: current methodological landscape
Open accessAbstract
Combination therapies exploit the chances for better efficacy, decreased toxicity, and reduced development of drug resistance and owing to these advantages, have become a standard for the treatment of several diseases and continue to represent a promising approach in indications of unmet medical need. In this context, studying the effects of a combination of drugs in order to provide evidence of a significant superiority compared to the single agents is of particular interest. Research in this field has resulted in a large number of papers and revealed several issues. Here, we propose an overview of the current methodological landscape concerning the study of combination effects. First, we aim to provide the minimal set of mathematical and pharmacological concepts necessary to understand the most commonly used approaches, divided into effect‐based approaches and dose–effect‐based approaches, and introduced in light of their respective practical advantages and limitations. Then, we discuss six main common methodological issues that scientists have to face at each step of the development of new combination therapies. In particular, in the absence of a reference methodology suitable for all biomedical situations, the analysis of drug combinations should benefit from a collective, appropriate, and rigorous application of the concepts and methods reviewed here.
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Experimental studies can effectively demonstrate networked mechanisms of action, synergistic or additive activity, and acceptable safety at clinically achievable drug concentrations.
“As an alternative to the in silico modeling, purposely addressed experimental studies can effectively demonstrate networked mechanisms of action, synergistic or additive activity, and acceptable safety at clinically achievable drug concentrations.45”
From From combinations to multitarget-directed ligands: A continuum in Alzheimer’s disease polypharmacology (2021) · cites this paper as [45]
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- Authors
- Foucquier, J., & Guedj, M.
- Affiliations
- Pharnext (France) (FR)
- Department of Bioinformatics and Biostatistics Pharnext Issy‐Les‐Moulineaux France
- Corresponding author
- Foucquier, Julie
- Venue
- Pharmacology Research & Perspectives
- Publisher
- Wiley
- Published
- 2015-05-20
- Volume
- 3
- Issue
- 3
- Pages
- e00149-e00149
- ISSN
- 2052-1707 (ISSN-L)
- PMC
- PMC4492765
- OpenAlex
- W1578932543
- Cited by
- 1,115
- References
- 68
- Citations by year
- 2026: 111 · 2025: 98 · 2024: 105 · 2023: 114 · 2022: 121 · 2021: 119 · 2020: 126 · 2019: 124 · 2018: 114 · 2017: 64 · 2016: 18 · 2015: 1
- FWCI
- 11.14
- Type
- journal article
- Language
- en
- Update notices
- correction (2019-11-26)
- Open access
- gold
- doi.org
- Licence
- Locations
- Pharmacology Research & Perspectives (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Strong
- National Cancer Institute (F31CA260794)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Keywords
- combination therapy, synergistic effect, effects-based approach, drug resistance, methodological issues
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