Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/35986
Title: | Statistical detection of synergy: New methods and a comparative study | Authors: | THAS, Olivier Tourny, Annelies Verbist, Bie Hawinkel, Stijn Nazarov, Maxim Mutambanengwe, Kathy BIJNENS, Luc |
Issue Date: | 2022 | Publisher: | WILEY | Source: | PHARMACEUTICAL STATISTICS, 21(2), p. 345-360 | Abstract: | Combination therapies are increasingly adopted as the standard of care for various diseases to improve treatment response, minimise the development of resistance and/or minimise adverse events. Therefore, synergistic combinations are screened early in the drug discovery process, in which their potential is evaluated by comparing the observed combination effect to that expected under a null model. Such methodology is implemented in the BIGL R-package which allows for a quick screening of drug combinations. We extend the meanR and maxR tests from this package by allowing non-constant variance of the responses and by extending the list of null models (Loewe, Loewe2, HSA, Bliss). These new tests are evaluated in a comprehensive simulation study under various models for additivity and synergy, various monotherapeutic dose-response models (complete, partial and incomplete responders) and various types of deviation from the constant variance assumption. In addition, the BIGL package is extended with bootstrap confidence intervals for the individual off-axis points and for the overall synergy strength, which were demonstrated to have reliable coverage and can complement the existing tests. We conclude that the differences in performance between the different null models are small and depend on the simulation scenario. As a result, the choice of null model should be driven by expert knowledge on the particular problem. Finally, we demonstrate the new features of the BIGL package and the difference between the synergy models on a real dataset from drug discovery. The BIGL package is available at CRAN () and as a Shiny app (). | Notes: | Hawinkel, S (corresponding author), Univ Ghent, Dept Data Anal & Math Modelling, Coupure Links 653, B-9000 Ghent, Belgium. stijn.hawinkel@psb.vib-ugent.be |
Keywords: | simulation study;statistical tests;synergy | Document URI: | http://hdl.handle.net/1942/35986 | ISSN: | 1539-1604 | e-ISSN: | 1539-1612 | DOI: | 10.1002/pst.2173 | ISI #: | WOS:000703232600001 | Rights: | 2021 John Wiley & Sons Ltd | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2022 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Pharmaceutical Statistics - 2021 - Thas - Statistical detection of synergy New methods and a comparative study.pdf Restricted Access | Published version | 2.05 MB | Adobe PDF | View/Open Request a copy |
WEB OF SCIENCETM
Citations
2
checked on Apr 22, 2024
Page view(s)
18
checked on Mar 21, 2022
Download(s)
2
checked on Mar 21, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.