Comparison of null models for combination drug therapy reveals Hand model as biochemically most plausible

Sinzger, Mark; Vanhoefer, Jakob; Loos, Carolin; Hasenauer, Jan

doi:10.1038/s41598-019-38907-x

Cited by 20 publications

(58 citation statements)

References 35 publications

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“…It is obvious, that the scores based on Bliss Independence are larger than those of Loewe Additivity and mainly above zero. This is due to the more conservative null reference surface as derived from Bliss Independence [see Sinzger et al (2019), Figure 6 ]. The scores from models that are based on Loewe Additivity are very similar to each other, as they scatter along the diagonal (panels in middle right and lower row).…”

Section: Resultsmentioning

confidence: 99%

“…During the analysis, we observed higher synergy scores when applying the Bliss Independence principle as null reference model. This is due to the more conservative null reference surface as derived from Bliss Independence [see exemplary comparison of isoboles from most of the models discussed here in (Sinzger et al, 2019, Figure 6 )]. Due to the synergy scores being relatively high, a differentiation between categories based on the synergy score poses a bigger challenge.…”

Section: Discussionmentioning

confidence: 99%

“…There is an increase in theoretical approaches to synergy, such as the recently re-discovered Hand model (Hand, 2000; Sinzger et al, 2019), which is a formulation of Loewe Additivity in form of a differential expression, or new ways of defining and measuring synergy, such as the ZIP model (Yadav et al, 2015), SynergyFinder (He and Tang, 2016), MuSyC (Meyer et al, 2019), and the copula model (Lambert and Dawson, 2019). It would be a large effort to compare these recent approaches with ours.…”

Section: Introductionmentioning

confidence: 99%

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Additive Dose Response Models: Defining Synergy

2019

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In synergy studies, one focuses on compound combinations that promise a synergistic or antagonistic effect. With the help of high-throughput techniques, a huge amount of compound combinations can be screened and filtered for suitable candidates for a more detailed analysis. Those promising candidates are chosen based on the deviance between a measured response and an expected non-interactive response. A non-interactive response is based on a principle of no interaction, such as Loewe Additivity or Bliss Independence. In a previous study, we introduced, an explicit formulation of the hitherto implicitly defined Loewe Additivity, the so-called Explicit Mean Equation. In the current study we show that this Explicit Mean Equation outperforms the original implicit formulation of Loewe Additivity and Bliss Independence when measuring synergy in terms of the deviance between measured and expected response, called the lack-of-fit. Further, we show that computing synergy as lack-of-fit outperforms a parametric approach. We show this on two datasets of compound combinations that are categorized into synergistic, non-interactive, and antagonistic.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Additive Dose Response Models: Defining Synergy

2019

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“…The most common candidates for the non-interactive response models are the Loewe additivity and Bliss independence models. However, there are other candidates such as the Highest Single Agent (HSA), the Tallarida and the recently rediscovered Hand model [20].…”

mentioning

confidence: 99%

“…We construct the null reference model numerically using the Hand model [20] by locally inverting the GP-fitted monotherapeutic data. Synergy is then assessed by a synergy effect surface as the difference between the GP-fitted response surface and the Hand-constructed null reference surface.…”

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confidence: 99%

Non-parametric synergy modeling with Gaussian processes

Shapovalova

Heskes

Dijkstra

2021

Preprint

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Background: Understanding the synergetic and antagonistic effects of combinations of drugs and toxins is vital for many applications, including treatment of multifactorial diseases and ecotoxicological monitoring. Synergy is usually assessed by comparing the response of drug combinations to a predicted non-interactive response from reference (null) models. Possible choices of null models are Loewe additivity, Bliss independence and the recently rediscovered Hand model. A different approach is taken by the MuSyC model, which directly fits a generalization of the Hill model to the data. All of these models, however, fit the dose-response relationship with a parametric model. Results: We propose the Hand-GP model, a non-parametric model based on the combination of the Hand model with Gaussian processes. We introduce a new logarithmic squared exponential kernel for the Gaussian process which captures the logarithmic dependence of response on dose. From the monotherapeutic response and the Hand principle, we construct a null reference response and synergy is assessed from the difference between this null reference and the Gaussian process fitted response. We evaluated performance of our model on a simulated data from Greco, two simulated data sets of our own design and two benchmark data sets from Chou and Talalay. We compare the Hand-GP model to standard synergy models and show that our model performs better than these standards. We also compare our model to the MuSyC model as example of a recent method which also fits a complete dose-response surface. Also in this case, the Hand-GP model performs better. Conclusion: The Hand-GP model is a flexible model to capture synergy. Its non-parametric natures allows it to model a wide variety of response patterns.

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Mathematical properties of Hand Incremental Effect Additivity and other synergy theories

Hanin

Xie

Sachs

2023

Math Methods in App Sciences

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Synergy theories for multi‐component agent combinations use 1‐agent dose‐effect relations (DERs), known from analyzing previous 1‐agent experiments, to calculate neither‐synergy‐nor‐antagonism combination DERs. Synergy theories are widely used in pharmacology, toxicology, and radiation biology. This article analyzes mathematical properties of one important synergy theory, proposed by John Hand in a little‐known article published in 2000 and here called Hand Incremental Effect Additivity (HIEA). In 2018, Hand's approach was reinvented in a radiobiology study that inadvertently overlooked his paper. We carefully state the assumptions required for mathematically rigorous development of HIEA and other synergy theories. Under these assumptions, studying synergy/antagonism between any number of agents can be done on a single 2d plot. We show that HIEA combination DER is in general not well‐defined in that it can “blow up” at finite total dose. We also formulate necessary and sufficient conditions on 1‐agent DERs preventing such pathology. Using weighted harmonic means, we study the betweenness property of HIEA synergy theory and demonstrate that Hand's combination DER has a systematic tendency for betweenness violation. On the positive side, we introduce the concept of a strongly dominant agent and show that the presence of such an agent ensures the betweenness property. We show also that the betweenness property holds for another major synergy theory, Loewe–Berenbaum Additivity. Our emphasis in this article on synergy theories that can handle any number of agents was motivated by applications to the study of toxic effects of galactic cosmic rays on astronauts during interplanetary travel.

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Comparison of null models for combination drug therapy reveals Hand model as biochemically most plausible

Cited by 20 publications

References 35 publications

Additive Dose Response Models: Defining Synergy

Additive Dose Response Models: Defining Synergy

Non-parametric synergy modeling with Gaussian processes

Mathematical properties of Hand Incremental Effect Additivity and other synergy theories

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