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Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics

PURPOSE: Quantification of pharmacodynamic interactions is key in combination therapies, yet conventional checkerboard experiments with up to 10 by 10 combinations are labor-intensive. Therefore, this study provides optimized experimental rhombic checkerboard designs to enable an efficient interacti...

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Autores principales: Kroemer, Niklas, Aubry, Romain, Couet, William, Grégoire, Nicolas, Wicha, Sebastian G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780134/
https://www.ncbi.nlm.nih.gov/pubmed/36163408
http://dx.doi.org/10.1007/s11095-022-03396-7
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author Kroemer, Niklas
Aubry, Romain
Couet, William
Grégoire, Nicolas
Wicha, Sebastian G.
author_facet Kroemer, Niklas
Aubry, Romain
Couet, William
Grégoire, Nicolas
Wicha, Sebastian G.
author_sort Kroemer, Niklas
collection PubMed
description PURPOSE: Quantification of pharmacodynamic interactions is key in combination therapies, yet conventional checkerboard experiments with up to 10 by 10 combinations are labor-intensive. Therefore, this study provides optimized experimental rhombic checkerboard designs to enable an efficient interaction screening with significantly reduced experimental workload. METHODS: Based on the general pharmacodynamic interaction (GPDI) model implemented in Bliss Independence, a novel rhombic ‘dynamic’ checkerboard design with quantification of bacteria instead of turbidity as endpoint was developed. In stochastic simulations and estimations (SSE), the precision and accuracy of interaction parameter estimations and classification rates of conventional reference designs and the newly proposed rhombic designs based on effective concentrations (EC) were compared. RESULTS: Although a conventional rich design with 20-times as many combination scenarios provided estimates of interaction parameters with higher accuracy, precision and classification rates, the optimized rhombic designs with one natural growth scenario, three monotherapy scenarios per combination partner and only four combination scenarios were still superior to conventional reduced designs with twice as many combination scenarios. Additionally, the rhombic designs were able to identify whether an interaction occurred as a shift on maximum effect or EC50 with > 98%. Overall, effective concentration-based designs were found to be superior to traditional standard concentrations, but were more challenged by strong interaction sizes exceeding their adaptive concentration ranges. CONCLUSION: The rhombic designs proposed in this study enable a reduction of resources and labor and can be a tool to streamline higher throughput in drug interaction screening. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11095-022-03396-7.
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spelling pubmed-97801342022-12-24 Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics Kroemer, Niklas Aubry, Romain Couet, William Grégoire, Nicolas Wicha, Sebastian G. Pharm Res Original Research Article PURPOSE: Quantification of pharmacodynamic interactions is key in combination therapies, yet conventional checkerboard experiments with up to 10 by 10 combinations are labor-intensive. Therefore, this study provides optimized experimental rhombic checkerboard designs to enable an efficient interaction screening with significantly reduced experimental workload. METHODS: Based on the general pharmacodynamic interaction (GPDI) model implemented in Bliss Independence, a novel rhombic ‘dynamic’ checkerboard design with quantification of bacteria instead of turbidity as endpoint was developed. In stochastic simulations and estimations (SSE), the precision and accuracy of interaction parameter estimations and classification rates of conventional reference designs and the newly proposed rhombic designs based on effective concentrations (EC) were compared. RESULTS: Although a conventional rich design with 20-times as many combination scenarios provided estimates of interaction parameters with higher accuracy, precision and classification rates, the optimized rhombic designs with one natural growth scenario, three monotherapy scenarios per combination partner and only four combination scenarios were still superior to conventional reduced designs with twice as many combination scenarios. Additionally, the rhombic designs were able to identify whether an interaction occurred as a shift on maximum effect or EC50 with > 98%. Overall, effective concentration-based designs were found to be superior to traditional standard concentrations, but were more challenged by strong interaction sizes exceeding their adaptive concentration ranges. CONCLUSION: The rhombic designs proposed in this study enable a reduction of resources and labor and can be a tool to streamline higher throughput in drug interaction screening. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11095-022-03396-7. Springer US 2022-09-26 2022 /pmc/articles/PMC9780134/ /pubmed/36163408 http://dx.doi.org/10.1007/s11095-022-03396-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Research Article
Kroemer, Niklas
Aubry, Romain
Couet, William
Grégoire, Nicolas
Wicha, Sebastian G.
Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics
title Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics
title_full Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics
title_fullStr Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics
title_full_unstemmed Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics
title_short Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics
title_sort optimized rhombic experimental dynamic checkerboard designs to elucidate pharmacodynamic drug interactions of antibiotics
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780134/
https://www.ncbi.nlm.nih.gov/pubmed/36163408
http://dx.doi.org/10.1007/s11095-022-03396-7
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