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Additive Dose Response Models: Explicit Formulation and the Loewe Additivity Consistency Condition

Overview of attention for article published in Frontiers in Pharmacology, February 2018
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Title
Additive Dose Response Models: Explicit Formulation and the Loewe Additivity Consistency Condition
Published in
Frontiers in Pharmacology, February 2018
DOI 10.3389/fphar.2018.00031
Pubmed ID
Authors

Simone Lederer, Tjeerd M. H. Dijkstra, Tom Heskes

Abstract

High-throughput techniques allow for massive screening of drug combinations. To find combinations that exhibit an interaction effect, one filters for promising compound combinations by comparing to a response without interaction. A common principle for no interaction is Loewe Additivity which is based on the assumption that no compound interacts with itself and that two doses from different compounds having the same effect are equivalent. It then should not matter whether a component is replaced by the other or vice versa. We call this assumption the Loewe Additivity Consistency Condition (LACC). We derive explicit and implicit null reference models from the Loewe Additivity principle that are equivalent when the LACC holds. Of these two formulations, the implicit formulation is the known General Isobole Equation (Loewe, 1928), whereas the explicit one is the novel contribution. The LACC is violated in a significant number of cases. In this scenario the models make different predictions. We analyze two data sets of drug screening that are non-interactive (Cokol et al., 2011; Yadav et al., 2015) and show that the LACC is mostly violated and Loewe Additivity not defined. Further, we compare the measurements of the non-interactive cases of both data sets to the theoretical null reference models in terms of bias and mean squared error. We demonstrate that the explicit formulation of the null reference model leads to smaller mean squared errors than the implicit one and is much faster to compute.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 84 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 18%
Student > Ph. D. Student 13 15%
Student > Bachelor 10 12%
Student > Master 7 8%
Student > Doctoral Student 5 6%
Other 10 12%
Unknown 24 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 20%
Agricultural and Biological Sciences 10 12%
Pharmacology, Toxicology and Pharmaceutical Science 7 8%
Medicine and Dentistry 6 7%
Chemistry 5 6%
Other 11 13%
Unknown 28 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 February 2018.
All research outputs
#20,462,806
of 23,020,670 outputs
Outputs from Frontiers in Pharmacology
#10,237
of 16,332 outputs
Outputs of similar age
#375,398
of 437,329 outputs
Outputs of similar age from Frontiers in Pharmacology
#189
of 290 outputs
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