What is the difference between synergism and antagonism

F—H Quantification of propidium iodide staining. Data are averages of three independent replicates. I—L Growth curves of C. Each experiment contained four technical replicates that were inoculated from the same culture. The lines represent the average of two experiments are presented in the figure. Source data are in Figure 6—source data 1. M Quantification of percent of dead cells after treatment with dicyclomine, FLZ, or synergy after 3, 9, and 24 hr.

Growth rate of cells grown in the presence of toxic amino acid analog 5-FAA. OD from each of two different biological replicates. These data were averaged to produce the graphs in Figure 6I—L. Colony forming units CFUs of C. If amino acid permeases are not localized to the plasma membrane, fungal cells are resistant to toxic amino acid analogs Roberg et al.

Finally, we tested whether dicyclomine is able to kill C. FLZ is fungistatic, inhibiting the growth the C. Since synergistic interactions can cause fungistatic drugs to switch to fungicidal Cowen et al. As a control, we tested the fungicidal drug amphotericin B Gray et al. Dicyclomine only caused cell death after 3 hr at a very high dose Figure 6—figure supplement 2A,E. We saw no increase in death of C.

After a 3 hr treatment, we did not observe an increase in cell death with the combination Figure 6—figure supplement 2C,G. Thus, we also sought to determine fungal cell death after 3, 9, and 24 hr of treatment. After 9 hr of treatment, we found that C. However, after 9- and 24 hr treatment, the combination had significantly more cell death than untreated or single agent-treated cells Figure 6—figure supplement 2M ; Figure 6M. Thus, our synergistic combination is fungicidal. Between 8- and 40 days post-inoculation d.

We used doses of both FLZ and dicyclomine which were within the range of doses given to humans Lexicomp, a ; Lexicomp, b. Dicyclomine alone did not affect mouse survival compared to PBS-treatment. However, dicyclomine in combination with FLZ significantly improved survival over FLZ alone in a dose-dependent manner Figure 7 , indicating that dicyclomine is not effective at treating cryptococcosis on its own, but could well be of therapeutic benefit when combined with FLZ.

Synergistic combination therapies are increasingly important clinical options, especially for drug resistant microbes Cowen and Lindquist, ; Kalan and Wright, ; Uppuluri et al.

Traditionally, synergistic drug pairs were discovered serendipitously, but new methods are improving our ability to uncover important interactions Brown et al. In this study, we identified a wide variety of molecules that interact synergistically with the antifungal FLZ to inhibit fungal growth.

We do so without the use of noisy multi-drug assays, allowing for rapid and scalable screening. We also identify and investigate antagonistic interactions, which are clinically important Khandeparkar and Rataboli, ; Vadlapatla et al. This work and our application of O2M to antibiotic trimethoprim Wambaugh et al. Here, one of the known synergizers used to identify synergy prediction genes, sertraline, inhibits phospholipase activity in Saccharomyces cerevisiae , which inhibits vesicle formation Rainey et al.

This could limit the range of synergizers identified by O2M. However, our studies on the trimethoprim demonstrates that identifying synergizers that phenocopy the downstream effect of known synergistic pairs, but target different factors, will bypass resistance to the starting synergizers due to the new targets Wambaugh et al. Of the 59 FLZ interacting molecules we identified, 10 have been previously described in various fungi. Of those 10, three were reported as synergists but antagonized FLZ activity in our assays Ahmad et al.

Prior work found that a single small molecule can both synergize with and antagonize the activity of a second small molecule depending on the concentration Meletiadis et al. This phenomenon could explain the difference in some of our results compared to previous published interactions. We found that structural similarity predicts synergistic interactions Figure 3 , just as drugs of similar structure have similar function.

These data demonstrate that many additional synergizers and antagonizers can be identified from a single example. Furthermore, we identified broad spectrum interactions. All the combinations tested showed efficacy against multiple clinical and environmental isolates of C. We also tested our combinations against common Candida species that often develop multi-drug resistance Colombo et al.

Our data demonstrate that FLZ synergizers and antagonizers exhibit broad activities against multiple species and isolates.

We investigated the antagonistic interaction between FLZ and nafcillin, a beta-lactam antibiotic commonly used against Staphylococcus aureus and other difficult-to-treat bacterial infections Letourneau, Patients with these infections include some of the same patients at risk for cryptococcosis HIV and cancer patients Kaplan et al.

This is above the concentration needed to achieve antagonism in vitro and could prove problematic in patients. When we examined nafcillin-related molecules, we found that methicillin and oxacillin also antagonize FLZ.

Furthermore, two cephalosporins often used in place of nafcillin, cefonicid and cefazolin, also unexpectedly antagonize fluconazole activity. Rifampicin is a potent inducer of drug metabolism due to elevation of hepatic cytochrome P through increased gene expression Bolt, In a recent autopsy study, 10 or 16 patients who died of cryptococcosis were administered either a penicillin or a cephalosporin Hurtado et al.

We recommend that these patients receive linezolid or vancomycin instead, since these drugs are used for similar bacterial targets but do not antagonize fluconazole activity Figure 5N. Our data demonstrate that O2M identifies promising new antifungal treatments that can rapidly move into the clinic. Dicyclomine is orally bioavailable and able to cross the blood brain barrier Das et al. Since dicyclomine, like many of our new FLZ synergizers, is approved by the FDA for other indications, it could rapidly move into the clinic.

In sum, O2M considerably streamlined the identification of important drug interactions affecting C. These interactions are both synergistic and antagonistic among multiple fungal species capable of causing disease in humans. We focused on FDA-approved molecules to bypass the time and considerable expense it takes to develop a new drug Pushpakom et al. However, our method would work equally well on any library of small molecules or biologic drugs to discover new antifungals.

We showed that identifying these drug interactions can quickly lead to additional interacting pairs by examining structure Figure 3 or by investigating underlying mechanism Wambaugh et al. Finally, our newly discovered interaction of dicyclomine and FLZ exhibited therapeutic potential in vivo, demonstrating the clinical potential of fluconazole-containing synergistic pairs in the clinic. Screening, validation, and structurally similar assays were performed with CM18 lab strain of C.

Mechanistic studies were tested using the KN99 lab strain of C. Clinical and environmental isolates of C. John R. Small molecules that altered growth by absolute value 0. We found altered growth by 0.

Small molecules were dissolved in DMSO to their highest soluble concentration and gradients were diluted in 2-fold dilution series. We followed previously published methods Hsieh et al. This inoculum was used for all fungal species and strains. Checkerboards were read at 0 and 48 hr on a BioTek plate reader model Synergy H1 to measure the OD Candida albicans and Candida glabrata were read at 0, 24, and 48 hr. When testing for a synergistic interaction, the FICI is determined by the lowest scoring well in the plate.

The FICI-determining well must exhibit a 4-fold decrease in drug concentration for each drug compared to the MIC 90 of each drug alone. For antagonistic interactions, the FICI is determined by the highest scoring well in a plate. Repeated results were averaged for the average FICI. Outliers with a different result e. All replicates were performed on different days from independent stating cultures and are independent biological replicates.

FICI scores presented in the figures are the average of a minimum of two independent replicates. If two replicates do not yield the identical result i. Outlier scores are defined as those that differ from the majority of scores e. However, average these example scores would result in an FICI of 0.

As this average differs from the result of the majority of the FICI scores, the outlier is excluded from the calculation. Percent growth was calculated for fluconazole, combinations, or small molecules alone. We then determined if growth inhibition caused by the combination was equal or greater than growth inhibition of the small molecules alone.

Repeated results were averaged for the average Bliss score. Bliss scores presented in the figures are the average of a minimum of two independent replicates. Outlier Bliss scores are not included in the analysis they can skew the results.

A DMSO control was conducted each time a molecule was tested to ensure the assay was working correctly. All DMSO results were averaged for the final score. Water and n -heptane were added to each tube, vortexed, and the n -heptane layer was transferred to borosilicate glass tubes.

Biological replicates were grown on separate days from independent starting cultures. Plates were assessed at 1, 2, and 3 days for resistance. This was then sub-cultured into the various treatments vehicle control was either 0. Cultures were washed twice and resuspended in PBS. After 1 min, flow cytometry was performed. Experiments were repeated three times on separate days from a different starting culture for each experiment and thus represent biological replicates.

This was sub-cultured into either dicyclomine 0. Cells were then sub-cultured again into honeycomb plates with those previous treatments dicylomine, FLZ, Synergy, or Vehicle with either 20, 10, 5, 2. Cells were washed once more with PBS and assessed by flow cytometry. Significance determined with Mann-Whitney test.

This assay was adapted from McMullan et al. Cultures were stained for 15 min in the dark then washed and resuspended in PBS and assessed by flow cytometry. Each treatment was a combination of at least three independent experiments. The inoculum was prepared by culturing C. After 10 min, mice were removed from the thread and were administered atipamezole Antisedan i. Beginning 8 days post-inoculation, they received daily i. Dosages were determined from human doses Lexicomp, a ; Lexicomp, b.

All data generated or analyzed during this study are included in the manuscript and supporting files. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses. More than a million people, primarily with immunocompromised immune systems, die each year from invasive fungal infections, yet only a handful of antifungal drugs are currently available.

To address this problem, the authors used a high throughput method to identify drugs including many that are already FDA approved that interact either synergistically or antagonistically with fluconazole, a major, widely available, and multi-species active antifungal drug but one which requires long periods of treatment. The authors identified drugs that act synergistically with fluconazole as well as drugs that act antagonistically with it.

The identification and characterization of drug interactions for treating diverse types of fungal infections harbors substantial potential for improving patient outcomes. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Wendy Garrett as the Senior Editor.

The reviewers have opted to remain anonymous. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission. Thank you for submitting this interesting manuscript to eLife. All of us thought that the data is extensive and the results are conclusive and that the manuscript is potentially worthy of publication.

However, all of us also thought that the manuscript needs some additional work, especially in a clearly explaining what was done and why, and b interpreting and discussing the results. The part starting with the identification of general anti-cryptococcal molecules by O2M and everything following appears to combine different angles of thought that are presented without a unifying thread.

It would greatly help the reader of this manuscript if the method would be clearly described as to stand alone. Please explain how similar they have to be and how similarity was assessed. Please explain, how many and which ones were averaged, given that there are seven replicates for DMSO for example and some drugs have a mix of positive and negative scores.

Those gene deletion strains are then used to screen for other new drugs that have the same effect on the gene deletions. Points to be considered:. It would be useful to a reader to know the genes are a hypothetical gene and a nuclear pore gene. The significance of these genes is not obvious. However, the screen suggests that the synergy uses the same mechanisms as the known drug synergy.

Would not synergy by other mechanisms not affect the same two gene deletions and therefore not be detected in the screen. This should be discussed. The manuscript needs to describe and discuss this. It might be the same as the MIC90 — that might be expected.

It might be less than the first drug concentration used. That might be expected. But it should be available, not NA. Presumably these are real drug concentrations tested, not an extrapolation of tested drug concentrations.

Three significant digits for a drug concentration is somewhat unrealistic. That information should be easily obtained and would provide a check on the likely use of these drugs in humans. It should be stated in the legend. The same scale should be used for each panel. It is possible that the green drugs and purple drugs could have different X axis scales as long as they are all the same within each of the two colors.

This might best to put into the supplementary figures. If the structures stay, then indicate which structure goes with which drug without having to find it in the legend. Is the p value of 0. It is not usually to 3 significant digits. If that value is for Figure 4Q, what is the p value for Figure 4P? It should not be a figure panel. The text mentions Figure 6 with no mention of Figure 5. This should be resolved. Presumably the concentrations on the panels are for 5FAA.

This has also been referred to as noninteraction, and inertism Greco et al. An additive effect is generally considered as the baseline effect for synergy detection methods. It is the effect that is theoretically expected from the combination of multiple drugs when synergy is not present.

Although seemingly simple from its name, the idea of simply adding two, or more, effects together do not accurately reflect what happens realistically. The problem of mathematically defining additivity has been the center of controversy among leading researchers of this topic for the last century. However, there are two models that have prevailed and will further be described in the Reference Models section.

Along with these prevailing models, there are two additional terms, Loewe Additivity and Bliss Independence Greco et al. Loewe Additivity has also been referenced as dose additivity and Concentration Addition Cedergreen, Any significant deviation from additivity would be classified as synergy or antagonism.

It is often agreed upon that synergy can be defined as a combination effect that is greater than the additive effect expected from good knowledge of the individual drugs. Synergy has also been called superadditivity Tallarida, , potentiation, augmentation Berenbaum, , supra-additivity Geary, The term coalism is also sometimes used to refer to synergy when neither drug, or none of the drugs in mixtures of more than two chemicals, is effective on its own Greco et al.

There are also two distinctively termed ideas to describe synergy under the previously mentioned specific models. Those terms are Loewe Synergy and Bliss Synergy; the models from which the terms have been derived will be discussed further in Reference Models.

Antagonism is the opposite of synergy; it occurs when the combined effect of compounds is less than what would be expected.

In the biomedical world, it is often considered more of a negative scenario, as many researchers are looking to identify synergistic interactions among compounds for some sort of added therapeutic effect. However, in a toxicological sense, it may be beneficial to have an antagonistic effect in a mixture of chemicals.

Antagonism has also been named subadditivity Tallarida, , infra-additive Geary, , negative interaction, depotentiation and even negative synergy Berenbaum, Synonyms used in discussions of synergy, additivity, and antagonism are summarized in Table 1. Central to some of the methods subsequently discussed is the idea of a dose-response relationship modeled as a curve.

This curve is referred to as a dose-response curve, dose-effect curve, concentration-effect curve or concentration-response curve Chou et al. These terms are sometimes used interchangeably Aronson, , but often coincide with the definitions of a dose being the amount of agent administered or experimentally used while a concentration is the measurable amount typically per some volume of substance in the experimental system Nielsen and Friberg, The experimental system could be an intact organism such as a mouse, or a model system such as lymphoblastoid cell lines, the latter of which has been implicated on various occasions as a viable, high-throughput model for assessing individual drug cytotoxicity Peters et al.

A common mathematical model when modeling the dose-response relationship, such as the cytotoxic effect of anticancer agents on cell viability, is the Hill model Konkoli, ; Beam and Motsinger-Reif, This model was first developed by Hill in as a model for percent of hemoglobin saturated with oxygen and is now widely used in biological sciences to model various processes, specifically in the form of the Michaelis-Menten equation describing the relationship between enzyme and substrates Goutelle et al.

This model has also been mathematically rewritten, and even directly referred to, as the sigmoid E max model, or simply the E max model or sigmoidal model Goutelle et al. The general equation for this model is given in Equation 1 , where E is the predicted response of the agent on the system, E 0 is the baseline response for a drug concentration of 0, E max is the maximum response, C is the concentration used for the predicted response E , and EC 50 is the concentration for which 50 percent of the maximal response is obtained, and h is the hill coefficient of sigmoidicity, also referred to as the slope parameter, which affects the shape of the curve Goutelle et al.

Examples of this curve and how the slope parameter can shape it are shown in Figure 1. It is also worth noting that while modeling dose-response curves is often a necessary step in many of the synergy detection methods, it is not always a simple task, especially when the curves are nonlinear. However, there have been various approaches to optimizing this procedure, such as an evolutionary algorithm method EADRM developed by Beam and Motsinger-Reif Figure 1.

Example of curves following the Hill equation with different hill slope parameter values. This serves as the baseline for quantifying how an interaction between two drugs should occur based on their individual performance, i. Deviation from the reference model can then be seen as some sort of synergistic or antagonistic interaction, depending on the direction of the deviation. There have been many attempts at trying to define the best reference model for the general case as well as for specific situations.

However, when considering how drugs interact within the human body, for example, many things are to be considered. Where the drugs are metabolized, the specific target s , etc. Unfortunately, a specific reference model cannot take into account every detail of how drugs may interact, and the more general models have prevailed. Throughout the past century, numerous reference models for additive drug interactions have been proposed, however there are two generally accepted models Greco et al.

Those two models, described as follows, are the Bliss Independence model and the Loewe Additivity model. In this type of mixture, there is not expected to be any sort of interaction since a single drug, or various similar drugs, cannot interact with itself, or each other Loewe, Thus, the result of a drug combined with itself is called Loewe Additivity. A similar drug would be one with perhaps similar structure and target.

This reference model is the basis for many commonly applied methods to detect synergy. As previously stated, it is generally considered one of the two most used reference models, potentially even the most accurate Greco et al.

However, there are limitations to the model which will be discussed later. The basic idea of Loewe Additivity assumes a drug cannot interact with itself. It is necessary to mention that this model assumes a constant potency ratio, which is the ratio of doses of two individual drugs that give the same effect.

It should be noted that in some literature, this has been referred to as a fixed ratio Hennessey et al. A given dose or concentration ex: EC 50 that produces a given effect can be measured on either curve. To do this, we must first convert the doses to the same curve. Thus, we have:. We can now use to either curve to calculate the effect of. This is the fundamental equation that has come out of the Loewe Additivity reference model.

It has been the basis for numerous subsequent models to quantify synergistic interactions. It also has led to the widely used combination index Loewe, , which is simply the left side of Equation 7. If the combination index is less than 1, synergy is said to occur, greater than 1, antagonism.

Additionally, this model can be extended to more than 2 compounds Berenbaum, ; Goldoni and Johansson, , where the equation becomes:. As with all models, there are limitations and assumptions made. One previously stated assumption is a constant potency ratio for the two dose response curves. As previously stated, curves with constant relative potency will have parallel log dose response curves Tallarida, ; Geary, ; Foucquier and Guedj, Parallel dose response curves and constant potency ratios are considered by some to rarely be the case or to be more of an exception Loewe, ; Geary, In fact, according to Geary, miniscule deviations from a constant potent ratio could result in a nonparallel log dose effect curves Geary, However, Grabovsky and Tallarida derived similar formulas for nonparallel log dose response curves to deal with such situations, though they may not be as simple as the general equation for constant potency ratios.

Furthermore, Loewe Additivity also requires that the dose response curves be accurately estimated individually for each drug in the combination Foucquier and Guedj, This is often not a trivial task. A further consideration when using Loewe Additivity is an indeterminate solution resulting, when the result from the conversion of dose A on curve Alpha to a new dose on curve Beta does not align with the conversion of dose B on curve Beta to a dose on curve Alpha Geary, According to Geary, this situation occurs frequently Geary, and can be illustrated more in-depth by him as well as Tallarida Tallarida, , ; Geary, Despite these limitations, Loewe Additivity has still been one of the major reference models used and the foundation for many synergy methods.

A commonly used alternative to Loewe Additivity is the Bliss Independence model. The Bliss model is based on the idea of noninteraction, that each drug is acting independently of one another Greco et al. However, this does not mean that they do not both potentially contribute to the overall effect, but presumably that they take different routes to achieve said effect.

An example originally described by Bliss involves an organism that dies from the effects of two distinct compounds. Under the idea of Bliss Independence, these compounds do not interact and perhaps affect different vital systems within the organism. Both compounds do affect the organism, however Bliss, The general form of the equation describing Bliss Independence is simply the product of the two fractional responses Greco et al.

Where F uc is the fraction unaffected by some outcome for the combination of drugs 1 and 2, f u 1 is the fraction unaffected for drug 1 and f u 2 is the fraction unaffected for drug two.

This can also be written in terms of the fraction affected by some event, as shown originally by Bliss :. Where F ac is the fraction affected by some outcome for the combination of drugs 1 and 2, f a 1 is the fraction affected for drug 1 and f a 2 is the fraction affected for drug two.

The two equations can be related by the following:. A more mathematical interpretation of this can be seen from understanding the idea of probabilistic independence Foucquier and Guedj, It is often appropriate to consider this problem in terms of probabilities because responses are often measured as fractions of living or killed components, for example fraction of cell death when administering anticancer drugs.

Given this, consider two compounds drugs, chemicals, etc. From probability theory,. Thus, combining Equations 11 and 12 , the common formula for Bliss Independence can be derived,.

Where E c is the effect produced by the combination of compounds A and B, at doses a and b, E a is the effect of compound A at dose a and E b is the effect of compound B at dose b. The above formula is often used as the reference for how a combination of compounds should act if no synergy or antagonism exists. If the combined effect is greater than what would be expected, as predicted from this formula, synergy is declared, antagonism otherwise.

Goldoni shows that this model can be expanded to numerous compounds, though the mathematics become increasingly complex upon using more than 3 compounds Goldoni and Johansson, Though still commonly used as a basic reference model, there has been much criticism over the validity of the Bliss Independence model. The main assumption of this model is that two drugs are acting independently. However, as asserted by Gessner , , for a large proportion of drug interactions, this may not truly be the case.

Additionally, for this model to hold true, it must be applicable along the entire dose response curve, something that may not be true in many cases Gessner, Advocates of the Loewe Additivity reference model often bring up an additional limitation of the Bliss Independence model. Aside from simply using the reference models as a baseline for additivity and deviations from that as a measure of synergy, specific methods have been developed for enhanced detection of synergy.

Here we discuss some of the more common methodologies along with their benefits and disadvantages. We then further discuss more recent, statistical approaches in a similar manner. One of the most prolific methods to come out of the Loewe Additivity reference model is the graphical procedure known as the isobologram method.

This type of analysis dates back to the late s with Fraser Fraser, — , and was continued by Loewe Loewe, ; Greco et al. An isobologram is a graphical procedure in which doses of one compound are displayed along one axis and doses of a second compound are displayed along the second axis. The entire plot contains combinations of doses for a specific effect level. This method relates to Loewe Additivity because Equation 5 is used to plot a line of additivity, the isobole Greco et al.

Dose combinations plotted below this line require a lower dose than expected from the Loewe Additivity line and thus can be classified as synergistic, while those plotted above it are antagonistic.

This can be seen in Figure 3. Figure 3. A Individual dose-response curves with EC 50 values and various points used in combination in B. B Isobologram showing line of additivity. Point W indicates synergy, point Q indicates additivity and point Z indicates antagonism. This method is very simple to achieve and a graphical, intuitive interpretation of synergy. However, there have been various drawbacks, further detailed in reviews by Greco et al.

We will briefly summarize these limitations here. One major drawback is that the approach is too simple for a majority of real world applications, as linear isoboles are relatively rare according to Loewe and Geary When dose response curves are nonparallel, as discussed under Loewe Additivity, a nonlinear isobole will result, referred to as a curvilinear isobole Grabovsky and Tallarida, ; Geary, Another major drawback is that this method lacks a formal statistical framework and does not allow for formally quantifying the intensity of a synergistic interaction Greco et al.

A similar, relatively popular Greco et al. This helps alleviate the problem of simple departures from the additivity line and while there are some other benefits to this method, it also has some of its own drawbacks, discussed more by Greco et al. The Chou-Talalay method is one of the most widely used methods for detecting and quantifying synergistic interactions between two or more drugs Greco et al.

According to Chou, the main equation forming the basis of this method was derived as a unified theory of the Michaelis-Menten, Hill, Henderson-Hasselbalch, and Scatchard equations Chou and Talalay, ; Chou, They termed this equation the median-effects equation:. This equation can be simplified into the following linearized version:. From this, values for D m and m can be estimated.

These values can then be used to calculate estimates for variables in the following equation giving the generalized combination index CI :. While D 1 and D 2 are known from experimental design, E 1 and E 2 can be calculated using the D m and m values previously computed. A CI value less than 1 indicates synergism, greater than 1 indicates antagonism, and equal to 1 indicating additivity.

Though one of the most prolific methods Greco et al. Among a number of limitations mentioned by Geary , this method requires drugs have a constant potency ratio Geary, Chou has asserted that a constant ratio is not strictly necessary, however a constant potency ratio does result in better accuracy Chou, First, he notes calculation of D m and m, shown in Equation 5 , from a median effects plot for mutually nonexclusive drugs can never be correct as dose response curves are primarily nonlinear.

Second, Greco shows that the form of one of the equations, for a specific set of parameters, used to calculate the combination index for the mutually nonexclusive case is slightly incorrect. The effect produced by the contrasting actions of two or more chemical groups.

An example of antagonistic effect is the effect between the opposing actions of insulin and glucagon to blood sugar level. While insulin lowers blood sugar glucagon raises it. What is synergy in medicine? Medical Definition of synergism : interaction of discrete agents as drugs such that the total effect is greater than the sum of the individual effects. Which would be the best example of synergism? The ability of acepromazine, a drug with little or no analgesic effects, to increase the analgesic effects of opioids e.

What drug is an antagonist? An antagonist is a drug that blocks opioids by attaching to the opioid receptors without activating them.

Antagonists cause no opioid effect and block full agonist opioids. Examples are naltrexone and naloxone. Naloxone is sometimes used to reverse a heroin overdose. What is an example of potentiation?

For example diazepam may potentiate the effect of alcohol. What causes synergism? Synergism comes from the Greek word "synergos" meaning working together. In toxicology, synergism refers to the effect caused when exposure to two or more chemicals at one time results in health effects that are greater than the sum of the effects of the individual chemicals. What is potentiation effect?

First one is a simple sum addition of effects, e.