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Synergistic and antagonistic drug interactions are important to consider when developing mixtures of anticancer or other types of drugs. Boik, Newman, and Boik (2008) proposed the MixLow method as an alternative to the Median-Effect method of Chou and Talalay (1984) for estimating drug interaction indices. One advantage of the MixLow method is that...
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... İlaç kombinasyonlarının analizinde özel bir yaklaşıma odaklanan örnekler mevcuttur. MixLow R paket programı, Loewe additif etki modelini önerir [58]. Çok sayıda çalışmada SAS [59] veya R kodlarının [60,61] kullanılmasından bahsedilmektedir. ...
Amaç: İlaç kombinasyon tedavisi, kanser gibi çeşitli ölümcül hastalıkların tedavisinde önemli rol oynamaktadır. İlaçlar kombine edildiğinde sinerjistik, additif veya antagonistik etkileşimler meydana gelir. Bu etkileşimlerin tanımlanması ve ilaç kombinasyonlarının kantitatif analizi basit değildir. Terminoloji, deneysel protokoller ve modellerin yanı sıra veri analizinde standardizasyon eksikliği başlıca sorunlardır. Bu çalışmada, sinerjistik ilaç kombinasyonlarının incelenmesi ve analizi ile ilgili mevcut matematiksel ve istatistiksel yöntemler derlenmiştir. Takibinde, yaygın kullanılan yöntemleri anlamak için gerekli olan farmakolojik ve matematiksel kavramlar da derlenmiş, avantaj ve dezavantajları tartışılmıştır. Son olarak ilaç kombinasyonlarının analizinde dikkat edilmesi gereken temel konular açıklanmıştır. Sonuç ve Tartışma: Muhtemel tüm deneysel koşullar için uygun optimum bir model olmadığı için, ilaç kombinasyonlarının kantitatif analizinin, burada tartışılan farklı yaklaşımların kollektif kullanımı ile kolaylaşacağını umuyoruz. Bu çalışmanın ilaç kombinasyonlarının analizi için bir referans teşkil edeceğine inanıyoruz.
... The MixLow method comes with the mixlow R package, which also includes functions for straigthforward data import and minimal data preprocessing, especially if the pattern suggested on the tray is followed during experimental design [68]. ...
In the past decades, many studies have examined the nature of the interaction between mycotoxins in biological models classifying interaction effects as antagonisms, additive effects, or synergisms based on a comparison of the observed effect with the expected effect of combination. Among several described mathematical models, the arithmetic definition of additivity and factorial analysis of variance were the most commonly used in mycotoxicology. These models are incorrectly based on the assumption that mycotoxin dose-effect curves are linear. More appropriate mathematical models for assessing mycotoxin interactions include Bliss independence, Loewe’s additivity law, combination index, and isobologram analysis, Chou-Talalays median-effect approach, response surface, code for the identification of synergism numerically efficient (CISNE) and MixLow method. However, it seems that neither model is ideal. This review discusses the advantages and disadvantages of these mathematical models.
... Herein, we discuss the advantages and limitations of these two major definitions, and then apply Bliss definition of independence for determination of statistically significant synergy in popular experimental and clinical trial settings in biology and medicine. Although several statistical packages in R for determination of synergy exist, such as hbim [6], mixlow [7], COMBIA [8], and (2) is troublesome because the uncertainty estimation of D 1A and D 1B is not taken into account. Moreover, the suggested grading of synergy based on the CI value, as suggested in [11], ignores the uncertainty of the CI estimation. ...
Although synergy is a pillar of modern pharmacology, toxicology, and medicine, there is no consensus on its definition despite its nearly one hundred-year history. Moreover, methods for statistical determination of synergy that account for variation of response to treatment are underdeveloped and if exist are reduced to the traditional t-test, but do not comply with the normal distribution assumption. We offer statistical models for estimation of synergy using an established definition of Bliss drugs’ independence. Although Bliss definition is well-known, it remains a theoretical concept and has never been applied for statistical determination of synergy with various forms of treatment outcome. We rigorously and consistently extend the Bliss definition to detect statistically significant synergy under various designs: (1) in vitro, when the outcome of a cell culture experiment with replicates is the proportion of surviving cells for a single dose or multiple doses, (2) dose-response methodology, (3) in vivo studies in organisms, when the outcome is a longitudinal measurement such as tumor volume, and (4) clinical studies, when the outcome of treatment is measured by survival. For each design, we developed a specific statistical model and demonstrated how to test for independence, synergy, and antagonism, and compute the associated p-value.
... As a consequence, the data should be taken with precautions, as can not be compared and properly discussed. To avoid this problem, the testing combinations of different agents should be conducted using standardized methods, such as time-kill method (CLSI, 1999;Verma, 2007), checkerboard method (Verma, 2007;EUCAST, 2000), Chou-Talalay method (Chou, 2010) or Boik method (Boik, 2010). All these methods possess some shortfalls, such as timeconsuming, labor-intensive, limitations regarding the number of the agents in combination, etc. ...
Eucalyptus has become one of the world's most widely planted genera and E. camaldulensis (The River Red Gum) is a plantation species in many parts of the world. The plant traditional medical application indicates great antimicrobial properties, so E. camaldulensis essential oils and plant extracts have been widely examined. Essential oil of E. camaldulensis is active against many Gram positive (0.07-1.1%) and Gram negative bacteria (0.01-3.2%). The antibacterial effect is confirmed for bark and leaf extracts (conc. from 0.08 μg/mL to 200 mg/mL), with significant variations depending on extraction procedure. Eucalyptus camaldulensis essential oil and extracts are among the most active against bacteria when compared with those from other species of genus Eucalyptus. The most fungal model organisms are sensitive to 0.125-1.0% of E. camaldulensis essential oil. The extracts are active against C. albicans (0.2-200 mg/mL leaf extracts and 0.5 mg/mL bark extracts), and against various dermatophytes. Of particular importance is considerable the extracts' antiviral activity against animal and human viruses (0.1-50 μg/mL). Although the antiprotozoal activity of E. camaldulensis essential oil and extracts is in the order of magnitude of concentration several hundred mg/mL, it is considerable when taking into account current therapy cost, toxicity, and protozoal growing resistance. Some studies show that essential oils' and extracts' antimicrobial activity can be further potentiated in combinations with antibiotics (beta-lactams, fluorochinolones, aminoglycosides, polymyxins), antivirals (acyclovir), and extracts of other plants (e.g. Annona senegalensis; Psidium guajava). The present data confirm the river red gum considerable antimicrobial properties, which should be further examined with particular attention to the mechanisms of antimicrobial activity.
... The combined effects of DON toxin and T-2 were analyzed by the MixLow method, and performed by the MixLow package in R (Boik & Narasimhan, 2010, 2014Team, 2014). In this method, the concentration-response curves are simulated by non-linear mixedeffects (nlm) model (Equations (1) and (2)), and the estimated Loewe indices are calculated from the parameters of nlm models (Equation (3)). ...
... ψ d,φ is the natural log concentration of individual drug d at the φ fraction affected value. More details could be found on the related papers and the interpretation of R package "mixlow" (Boik & Narasimhan, 2010, 2014. The mixture is indicative of synergism if the estimated Loewe index L φ is less than 0.9, strong synergism if less than 0.3, additivity if between 0.9 and 1.1, antagonism if larger than 1.1, and strong antagonism if larger than 3.3. ...
Deoxynivalenol (DON) and T‐2 toxin are prevalent mycotoxin contaminants in the food and feed stuffs worldwide, with non‐negligible co‐contamination and co‐exposure conditions. Meanwhile, they are considerable risk factors for Kashin‐Beck disease, a chronic endemic osteochondropathy. The aim of this study was to investigate the individual and combined cytotoxicity of DON and T‐2 toxin on proliferating human C‐28/I2 and newborn rat primary costal chondrocytes by MTT assay. Four molar concentration combination ratios of DON and T‐2 toxin were used, 1:1 for R1 mixture, 10:1 for R10, 100:1 for R100 and 1000:1 for R1000. The toxicological interactions were quantified by the MixLow method. DON, T‐2 toxin, and their mixtures all showed a clear dose‐dependent toxicity for chondrocytes. The cytotoxicity of T‐2 toxin was 285‐fold higher than DON was in human chondrocytes, and 22‐fold higher in the rat chondrocytes. The combination of DON and T‐2 toxin was significantly synergistic at middle and high level concentrations of R10 mixtures in rat chondrocytes, but significantly antagonistic at the low concentrations of R100 mixtures in both cells and at the middle concentrations of R1000 mixtures in rat chondrocytes. These results indicated that the combined toxicity was influenced by the cell sensitivity for toxins, the difference between the combination ratio and equitoxic ratio, the concentrations and other factors. Deoxynivalenol (DON) and T‐2 toxin are prevalent mycotoxin contaminants and a risk factor for Kashin‐Beck disease. The individual and combined cytotoxicity of DON and T‐2 toxin were investigated on human C‐28/I2 and rat primary chondrocytes. The cytotoxicities of T‐2 toxin and DON are varied in different chondrocytes. Synergistic, antagonistic or additive toxicological interactions were observed in the binary mixture at different combination ratios. It suggested that the combined toxicity was influenced by cell sensitivity, combination ratios and concentrations.
... Additionally, some drug combination analysis programs stipulate that only data from fixed-concentration ratios be entered. 12 This restricts the breadth of data that can be collected from robust methods such as HTFC. Furthermore, results from drug combination analyses are often presented in two-dimensional diagrams, such as heatmaps, doseresponse x,y graphs for each concentration ratio tested, or tables of synergy statistics, 13,18 and therefore quick interpretation of the data may not be straightforward. ...
Classical therapeutic regimens are subject to toxicity, low efficacy, and/or the development of drug resistance. Thus, the discovery of synergistic drug combinations would permit treatment with lower, tolerable dosages of each agent and restored sensitivity. We describe the development and use of the SynScreen software application, which allows for visual and mathematical determinations of compound concentrations that produce super-additive effects. This software uses nonlinear regression fits of dose responses to determine synergism by the Bliss independence and Loewe additivity analysis models. We demonstrate the utility of SynScreen with data analysis from in vitro high-throughput flow cytometry (HTFC) combination screens with repurposed drugs and multiplexed synergy analysis of multiple biologic parameters in parallel. The applicability of SynScreen was confirmed by testing open-source data sets used in published drug combination literature. A key benefit of SynScreen for high-throughput drug combination screening is that observed measurements are graphically depicted in comparison with a three-dimensional surface that represents the theoretical responses at which Bliss additivity would occur. These images and summary tables for the calculated drug interactions are automatically exported. This allows for substantial data sets to be visually assessed, expediting the quick identification of efficacious drug combinations and thereby facilitating the design of confirmatory studies and clinical trials.
... To facilitate the data analysis of high-throughput drug combination screens, more recent tools have been made available as R implementations (https://www.R-project.org). For example, mixlow is an R package which utilizes a nonlinear mixed-effects model to calculate the CI [17]. However, mixlow works only for an experimental design where the ratio of two drugs in a combination is fixed over all tested concentrations. ...
Gene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Toward more effective treatment options, we will need multi-targeted drugs or drug combinations, which selectively inhibit the viability and growth of cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.
... To analyze the type of pharmacokinetic interactions of Dox and the extract in combination, the Loewe additivity model (LI) was used and data from the MTT assay were subjected to statistical analysis with the mixLow package in R-studio [19]. Data from apoptosis, cell cycle and Western blotting were analyzed by analysis of variance (ANOVA) using GraphPad Prism software. ...
Polygonum maritimum is a traditional herbal remedy that produces abundant flavonoid secondary metabolites. The ethanol extract of P. maritimum aerial parts (POM) was chemically characterized and tested for antimicrobial properties and cytotoxicity. Results of LC-MS/MS analysis showed high contents of gallic acid, epigallocatechin gallate and catechin, and significant amounts of quercetin-3-O-galactoside and quercetin-3-O-glucoside. Evaluation of the antifungal properties revealed that POM induced notable growth inhibition of Alternaria alternata (34.3%), Penicillium spp. (30.6%), Fusarium semitectum (20.2%) and Aspergillus spp. (19.6%). Evaluation of cytotoxicity against human hepatoma HepG2 cells included monitoring the effects of both POM alone and its combination with cytostatic doxorubicin (Dox). Cell viability, apoptosis and cell cycle distribution and the expression of antioxidant enzymes (superoxide-dismutases SOD1 and SOD2 and catalase) were determined. A dose-dependent decrease in cell viability was detected, but a remarkably stronger effect was obtained when POM and Dox were applied in combination as compared to individual treatments. IC50 values were determined to be 393 μg/mL (POM) and 2.24 μg/mL (Dox) in combination, but 1153 μg/mL (POM) and 12.56 μg/mL (Dox) in a single treatment. The value of the Loewe index, determined for IC50, was notably lower than 1 (LI=0.51), clearly indicating synergism of POM and Dox. Additionally, POM and POM +Dox induced early/late apoptosis and G2/M cell cycle arrest. Furthermore, POM increased, while Dox decreased the expression levels of SODs and catalase. The obtained results encourage further examination of the potential use of POM in modern phytotherapy. [Project of the Serbian Ministry of Education, Science and
Technological Development, Grant no. 172058]
... There are already a few other R packages available for combination synergy/antagonism calculations. The package mixlow implements the Loewe additivity model [11,12] for synergy/antagonism calculation [14] and the package hbim uses the Bliss independence model [10] for calculation of synergy while focusing on vaccines [15]. R package synergyfinder is offering analyses according to multiple models [30]. ...
We analyzed survival effects for 15 different pairs of clinically relevant anti-cancer drugs in three iso-genic pairs of human colorectal cancer carcinoma cell lines, by applying for the first time our novel software (R package) called COMBIA. In our experiments iso-genic pairs of cell lines were used, differing only with respect to a single clinically important KRAS or BRAF mutation. Frequently, concentration dependent but mutation independent joint Bliss and Loewe synergy/antagonism was found statistically significant. Four combinations were found synergistic/antagonistic specifically to the parental (harboring KRAS or BRAF mutation) cell line of the corresponding iso-genic cell lines pair.
COMBIA offers considerable improvements over established software for synergy analysis such as MacSynergy™ II as it includes both Bliss (independence) and Loewe (additivity) analyses, together with a tailored non-parametric statistical analysis employing heteroscedasticity, controlled resampling, and global (omnibus) testing.
In many cases Loewe analyses found significant synergistic as well as antagonistic effects in a cell line at different concentrations of a tested drug combination. By contrast, Bliss analysis found only one type of significant effect per cell line.
In conclusion, the integrated Bliss and Loewe interaction analysis based on non-parametric statistics may provide more robust interaction analyses and reveal complex patterns of synergy and antagonism.
... The first method developed by Boik et al. (2008), named MixLow (Mixed-effects Loewe), uses Loewe Additivity as the reference model. The method consists of three basic parts: estimation of dose response curve parameters, calculation of the Loewe Additivity index (i.e., combination index), and calculation of confidence intervals for the index (Boik, 2010). The method assumes a sigmoidal dose response curve and a nonlinear mixedeffects model is used to estimate curve parameters and then uses those parameters to estimate their Loewe Additivity Index and confidence intervals. ...
... This method has been favorably compared to the Chou-Talalay Method in simulation experiments (Boik et al., 2008). The major benefits of the MixLow method is that it avoids the necessary preprocessing of the Chou-Talalay method as well as avoiding the need for log-linearization (Boik, 2010). Limitations of this method may be assumptions of a sigmoidal dose response curve and the necessity for fixed-ratio drug combinations. ...
The idea of synergistic interactions between drugs and chemicals has been an important issue in the biomedical world for over a century. As complex diseases, especially cancer, are being treated with various drug cocktails, understanding the interactions among these drugs is increasingly vital to ensuring successful treatment regimens. However, the idea of synergy is not limited to only the biomedical realm and these ideas have developed across many different disciplines, as well. In this review, we first discuss the various terminology surrounding the idea of synergy, providing a comprehensive list of terms defined across numerous disciplines. We then review the most common methodology for detection and quantification of synergy, including the two most prominent reference models for describing additive interactions: Loewe Additivity and Bliss Independence. We also discuss advantages and limitations to each method, with a focus on the Chou-Talalay Combination Index method. Finally, we describe how methods development and terminology have developed among disciplines outside of biomedicine and pharmacology, to synthesize the literature for readers.
