ArticleScientific reports2017
BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
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- Systematic identification of biomarker-driven drug combinations to overcome resistance.Nature chemical biology · 2022Article
- Pharmacodynamics of Moxifloxacin, Meropenem, Caspofungin, and Their Combinations againstAntimicrobial agents and chemotherapy · 2022Article
- Exposure to human relevant mixtures of halogenated persistent organic pollutants (POPs) alters neurodevelopmental processes in human neural stem cells undergoing differentiation.Reproductive toxicology (Elmsford, N.Y.) · 2021Article
- Charting the Fragmented Landscape of Drug Synergy.Trends in pharmacological sciences · 2020Review
- Generalized concentration addition for ligands that bind to homodimers.Mathematical biosciences · 2019Article
- Comparison of null models for combination drug therapy reveals Hand model as biochemically most plausible.Scientific reports · 2019Article
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8 authors.
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Abstract
Clinical efficacy regularly requires the combination of drugs. For an early estimation of the clinical value of (potentially many) combinations of pharmacologic compounds during discovery, the observed combination effect is typically compared to that expected under a null model. Mechanistic accuracy of that null model is not aspired to; to the contrary, combinations that deviate favorably from the model (and thereby disprove its accuracy) are prioritized. Arguably the most popular null model is the Loewe Additivity model, which conceptually maps any assay under study to a (virtual) single-step enzymatic reaction. It is easy-to-interpret and requires no other information than the concentration-response curves of the individual compounds. However, the original Loewe model cannot accommodate concentration-response curves with different maximal responses and, by consequence, combinations of an agonist with a partial or inverse agonist. We propose an extension, named Biochemically Intuitive Generalized Loewe (BIGL), that can address different maximal responses, while preserving the biochemical underpinning and interpretability of the original Loewe model. In addition, we formulate statistical tests for detecting synergy and antagonism, which allow for detecting statistically significant greater/lesser observed combined effects than expected from the null model. Finally, we demonstrate the novel method through application to several publicly available datasets.
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