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A New Bliss Independence Model to Analyze Drug Combination Data
Open accessAbstract
The Bliss independence model is widely used to analyze drug combination data when screening for candidate drug combinations. The method compares the observed combination response (Y(O)) with the predicted combination response (Y(P)), which was obtained based on the assumption that there is no effect from drug-drug interactions. Typically, the combination effect is declared synergistic if Y(O) is greater than Y(P). However, this method lacks statistical rigor because it does not take into account the variability of the response measures and can frequently cause false-positive claims. In this article, we introduce a two-stage response surface model to describe the drug interaction across all dose combinations tested. This new method enables robust statistical testing for synergism at any dose combination, thus reducing the risk of false positives. The use of the method is illustrated through an application describing statistically significant "synergy regions" for candidate drug combinations targeting epidermal growth factor receptor and the insulin-like growth factor 1 receptor.
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“Even when replicates are available, multiple testing problems arise from repeatedly performing a statistical test across all combination doses (Zhao et al 2014).”
From Evaluation of Drug Combination Effect Using a Bliss Independence Dose–Response Surface Model (2018) · cites this paper as Zhao et al 2014
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“I Y Y M a b ab O ab P = − = + , , ( | , ) Γ ε, (3)”
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“The evaluation of the synergistic combination effect was conducted using the Bliss independence model [19, 20].”
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“In addition, analysis of the data presented in Figure 8 using the Highest Single Agent (HSA) model demonstrated positive effects across all cell lines, whereas the Bliss Independence model revealed synergistic interactions in all combinations of most cell lines (Table S2) [38–42].”
Clark, R., Saha, A., Hackman, G. L., Friedman, C. A., Gorgoglione, R., Tiziani, S., & DiGiovanni, J. (2026) · Molecular Carcinogenesis · doi:10.1002/mc.70087 · Cited by 2
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Xisto, M. I. D. D. S., Rollin‐Pinheiro, R., da Rosa, P. C. M., Santos, J. D. S., Irmão, N. F. D. S., Abib, J. A. A., Rochetti, V. P., de Castro-Almeida, Y., Freitas, G. M. P. D. S., Cypriano, J. B. S., et al. (2026) · Microbiology Spectrum · doi:10.1128/spectrum.03356-25 · Cited by 2
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“Report comprehensive dose–response matrices and employ the Chou–Talalay [10] or Bliss independence [235] methods.”
SİNERJİSTİK İLAÇ KOMBİNASYONLARININ ANALİZİNDE GÜNCEL MATEMATİKSEL VE İSTATİSTİKSEL YÖNTEMLER
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“We selected the Loewe synergy score as regression objective as the BLISS model are more likely to provide false positive results [50].”
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“Foldexcess additivismwascalculatedasa ratioofobserved toexpected values for drug combinations, where the expected value C is calculated from the Bliss algorithm for response to two compoundswith effects A and B that is C=A+ B−A × B [14].”
MethodWilliams, R. S. B., Schaf, J., Shinhmar, S., Zeng, Q., Pardo, O. E., Beesley, P. W., & Syed, N. (2022) · Research Square · doi:10.21203/rs.3.rs-2178722/v1 · Cited by 2
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“The combination of panduratin A and GS-5801 significantly inhibited HBV replication, confirmed by Bliss model analysis [62].”
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“Additionally, while various microorganism strains have been identified in the current FME, the microbiome is a highly complex ecosystem with in excess of 2000 species, is warranted [76, 77].”
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“To determine the synergistic, antagonistic or independent behaviour of the treatment, the predicted treatment efficiency (Y LED/NO,P ) was calculated according to the Bliss independence model [43] (Equation 3), where Y LED is the LED treatment and Y NO is the NO-releasing material.”
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“Some reports relied on single-concentration inhibition values, others reported EC₅₀ values without matched toxicity measurements, and relatively few applied formal synergy or resistance metrics [7, 8].”
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“In this model YAB,O > YAB,P means synergy, while YAB,O = YAB,P means additive effect [11].”
BackgroundMethodBioinformatic strategies to understand the complexities of medicinal natural product mixtures
Caesar, L. K. (2019) · NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro) · Cited by 1
Wilder, C. S., Chiou, J., Battenhouse, A. M., Saha, A., Chen, Z., Kim, E., Gadallah, M. I., Tiziani, S., Georgiou, G., Stone, E. M., et al. (2023) · Molecular Carcinogenesis · doi:10.1002/mc.23597 · Cited by 1
“The synergy of drug combinations was assessed with the widely utilized Bliss Independence model.(24) Statistical methods were used to predetermine the sample size for animal experiments.”
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Self-citationNovel Hormonal Combination Therapy for Triple Negative Breast Cancer
Thakkar, A. (2016)
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Cell-based models for studying paediatric high-grade gliomas
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Sadeghi, E., Raiesi, F., & Hossienpur, A. R. (2019) · JWSS - Isfahan University of Technology · doi:10.29252/jstnar.23.2.361
Stover, M. (2019) · Scholarship at UWindsor (University of Windsor)
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“As a reference case, we first present the Bliss independence model for the two-drug case (Zhao et al. 2014; Demidenko and Miller 2019).”
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“7 express wild type TP53, as determined by combination analysis (Bliss-independence model 124 (16)).”
Xu, F., Tong, M., Tong, C. S. W., Chan, B. K. C., Chu, H. Y., Wong, T. L., Fong, J. H. C., Cheung, M. S. H., Mak, K. H.-M., Pardeshi, L. A., et al. (2023) · doi:10.1158/0008-5472.22430385
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Shigeta, S., Lui, G. Y. L., Shaw, R. C., Moser, R. D., Gurley, K. E., Durenberger, G., Rosati, R., Diaz, R. L., Ince, T. A., Swisher, E. M., et al. (2023) · doi:10.1158/1535-7163.c.6543286.v1
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Shin, S., & Nguyen, L. K. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.07.536087
“These include the Coefficient of Drug Interaction (CDI) model (28, 29), the Bliss Independence (BI) model (30, 31), the Chou-Talalay model (32), highest single agent (HSA) model (33) and zero interaction potency (ZIP) model (34, 35).”
BackgroundMethodInfluentialTsikopoulos, A., Tsikopoulos, K., Meroni, G., Gravalidis, C., Soukouroglou, P., Chatzimoschou, A., Drago, L., Triaridis, S., & Papaioannidou, P. (2023) · Antibiotics · doi:10.3390/antibiotics12071103
“Synergy Assessment between Al2O3 and TiO2 The synergistic or antagonistic effects between Al2O3 and TiO2 were assessed in line with Bliss’s independence model [26].”
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Powell, R. T. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-824010-6.00063-0
Capper-Parkin, K. (2023) · Sheffield Hallam University · doi:10.7190/shu-thesis-00589
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Mo, H., Liu, X., Yu, X. F., Chen, H., Guo, S., Li, Z., Wang, S., Li, C., Han, J., Fu, M., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20745213
Mo, H., Liu, X., Yu, X. F., Chen, H., Guo, S., Li, Z., Wang, S., Li, C., Han, J., Fu, M., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20745204
Reduced mitochondrial transcription sensitizes acute myeloid leukemia cells to BCL-2 inhibitionPreprint
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“The chimeric measure has been widely used in the genetics literature (e.g. [23, 24, 25, 26, 27, 28, 29, 4, 30, 31, 32, 33, 34]) and in the drug interaction literature (e.g. [70, 71, 72, 73, 74, 75, 57, 43, 76, 77]).”
MethodRen, X., Li, J., Chen, L., Wang, X., Zhang, J., Zhang, Y., Fan, J., Yun, D., Zhang, C., Yu, S., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-5305574/v1
Padey, B., Droillard, C., Dulière, V., Fouret, J., de Lamballerie, C. N., Milesi, C., Laurent, E., Brun, P., Traversier, A., Julien, T., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.5041998
Combination Oxylanthanum Carbonate and Tenapanor Lowers Urinary Phosphate Excretion in Rats
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Reduced mitochondrial transcription sensitizes acute myeloid leukemia cells to BCL-2 inhibitionPreprint
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Fubylation as a Druggable Ubiquitin-Like Conjugation System Controlling Hippo Pathway ActivityPreprint
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“Interestingly, co-treatment of sCMF231 and PY-60, an ANXA2-inhibiting YAP activator previously identified by our group, synergistically activates TEAD-LUC reporter activity as determined by changes in Bliss independence calculations 36 (Fig.”
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“This is a notable feature of the Bliss independence model which distinguishes it from other commonly used models for determining synergy (34).”
Role of the ETV5/p38 Signaling Axis in Aggressive Thyroid Cancer Cells
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Metadata
- Authors
- Zhao, W., Sachsenmeier, K., Zhang, L., Sult, E., Hollingsworth, R. E., & Yang, H.
- Affiliations
- AbbVie (United States) (US)
- Corresponding author
- Zhao, Wei
- Venue
- SLAS Discovery
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 19
- Issue
- 5
- Pages
- 817-821
- ISSN
- 2472-5552 (ISSN-L)
- OpenAlex
- W1980181290
- Cited by
- 322
- References
- 14
- Citations by year
- 2026: 46 · 2025: 33 · 2024: 29 · 2023: 45 · 2022: 40 · 2021: 19 · 2020: 26 · 2019: 23 · 2018: 17 · 2017: 17 · 2016: 14 · 2015: 11 · 2014: 2
- FWCI
- 15.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- SLAS DISCOVERY (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- Bliss independence model, drug synergy, drug-drug interactions, false positive reduction, epidermal growth factor receptor, IGF-1 receptor, drug combination screening
- MeSH terms
- Algorithms, Antineoplastic Agents, Carcinoma, Non-Small-Cell Lung, Dose-Response Relationship, Drug, Drug Combinations, Drug Interactions, Drug Synergism, Humans, Lung Neoplasms, Models, Chemical, Neoplasms, Regression Analysis, Technology, Pharmaceutical, Signal Transduction, Receptor, IGF Type 1, Drug Resistance, Neoplasm, ErbB Receptors
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