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Analysis of drug combinations: current methodological landscape.

Foucquier J, Guedj M - Pharmacol Res Perspect (2015)

Bottom Line: 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.Here, we propose an overview of the current methodological landscape concerning the study of combination effects.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioinformatics and Biostatistics, Pharnext Issy-Les-Moulineaux, France.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Possible inconsistency in assessing drug synergy based on Response Additivity or Bliss Independence. Identical simulated dose–effect curve for two different drugs. Suppose that a dose = 4 of drug A results in 25% of effect, likewise for drug B. From Response Additivity, one would conclude in synergism with a combination effect above 50%. From Bliss Independence, one would conclude in synergism with a combination effect above 43%. However, note that either a dose = 2 × 4 = 8 of drug A or of drug B alone brings the effect up to 91%. Therefore, a total of dose = 8 of the hypothetical combined drug elicits less effect under Response Additivity or Bliss Independence than the same dose of either drug alone, yet one would conclude synergism.
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fig02: Possible inconsistency in assessing drug synergy based on Response Additivity or Bliss Independence. Identical simulated dose–effect curve for two different drugs. Suppose that a dose = 4 of drug A results in 25% of effect, likewise for drug B. From Response Additivity, one would conclude in synergism with a combination effect above 50%. From Bliss Independence, one would conclude in synergism with a combination effect above 43%. However, note that either a dose = 2 × 4 = 8 of drug A or of drug B alone brings the effect up to 91%. Therefore, a total of dose = 8 of the hypothetical combined drug elicits less effect under Response Additivity or Bliss Independence than the same dose of either drug alone, yet one would conclude synergism.

Mentions: The Response Additivity approach (also referred to as Linear Interaction Effect (Slinker 1998)) consists in showing that a positive drug combination effect occurs when the observed combination effect (EAB) is greater than the expected additive effect given by the sum of the individual effects (EA + EB) (Fig.1C). The Combination Index can be calculated as: , and the corresponding P-value is given by the significance of the interaction effect in a factorial analysis of variance of the individual and combination effects (Slinker 1998). The Response Additivity approach can appear as a natural improvement of the Highest Single Agent to assess synergy, as it compares the observed combination effect (EAB) to an expected effect from additivity instead of the effect of the single agents. It assumes that drugs have linear dose–effect curves with zero intercepts, which is generally not the case as most dose–effect curves are characterized by logistic or curvilinear shapes (Caudle and Williams 1993). To better understand the problem, Figure2 illustrates the simple and extreme case in which two dose–effect curves are identical and the combination effect is merely additive. Response Additivity would indicate synergism in the curved-up part and antagonism in the curved-down part, and would result in the following invalid and counterintuitive interpretation of the drug combination effect: a synergistic combination could be less effective than its components applied individually. Figure2 can also be used to illustrate the paradox of the sham combination of one drug with itself. Let’s say that a drug preparation is divided into two tubes, and then each tube is treated as if it contained a different drug with identical dose–effect curves. By using the same logic, one could conclude that the combination of the same drug with itself (obviously additive) is synergistic (Greco et al. 1995).


Analysis of drug combinations: current methodological landscape.

Foucquier J, Guedj M - Pharmacol Res Perspect (2015)

Possible inconsistency in assessing drug synergy based on Response Additivity or Bliss Independence. Identical simulated dose–effect curve for two different drugs. Suppose that a dose = 4 of drug A results in 25% of effect, likewise for drug B. From Response Additivity, one would conclude in synergism with a combination effect above 50%. From Bliss Independence, one would conclude in synergism with a combination effect above 43%. However, note that either a dose = 2 × 4 = 8 of drug A or of drug B alone brings the effect up to 91%. Therefore, a total of dose = 8 of the hypothetical combined drug elicits less effect under Response Additivity or Bliss Independence than the same dose of either drug alone, yet one would conclude synergism.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492765&req=5

fig02: Possible inconsistency in assessing drug synergy based on Response Additivity or Bliss Independence. Identical simulated dose–effect curve for two different drugs. Suppose that a dose = 4 of drug A results in 25% of effect, likewise for drug B. From Response Additivity, one would conclude in synergism with a combination effect above 50%. From Bliss Independence, one would conclude in synergism with a combination effect above 43%. However, note that either a dose = 2 × 4 = 8 of drug A or of drug B alone brings the effect up to 91%. Therefore, a total of dose = 8 of the hypothetical combined drug elicits less effect under Response Additivity or Bliss Independence than the same dose of either drug alone, yet one would conclude synergism.
Mentions: The Response Additivity approach (also referred to as Linear Interaction Effect (Slinker 1998)) consists in showing that a positive drug combination effect occurs when the observed combination effect (EAB) is greater than the expected additive effect given by the sum of the individual effects (EA + EB) (Fig.1C). The Combination Index can be calculated as: , and the corresponding P-value is given by the significance of the interaction effect in a factorial analysis of variance of the individual and combination effects (Slinker 1998). The Response Additivity approach can appear as a natural improvement of the Highest Single Agent to assess synergy, as it compares the observed combination effect (EAB) to an expected effect from additivity instead of the effect of the single agents. It assumes that drugs have linear dose–effect curves with zero intercepts, which is generally not the case as most dose–effect curves are characterized by logistic or curvilinear shapes (Caudle and Williams 1993). To better understand the problem, Figure2 illustrates the simple and extreme case in which two dose–effect curves are identical and the combination effect is merely additive. Response Additivity would indicate synergism in the curved-up part and antagonism in the curved-down part, and would result in the following invalid and counterintuitive interpretation of the drug combination effect: a synergistic combination could be less effective than its components applied individually. Figure2 can also be used to illustrate the paradox of the sham combination of one drug with itself. Let’s say that a drug preparation is divided into two tubes, and then each tube is treated as if it contained a different drug with identical dose–effect curves. By using the same logic, one could conclude that the combination of the same drug with itself (obviously additive) is synergistic (Greco et al. 1995).

Bottom Line: 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.Here, we propose an overview of the current methodological landscape concerning the study of combination effects.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioinformatics and Biostatistics, Pharnext Issy-Les-Moulineaux, France.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus