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A pharmacodynamic model of clinical synergy in multiple myeloma

BACKGROUND: Multiagent therapies, due to their ability to delay or overcome resistance, are a hallmark of treatment in multiple myeloma (MM). The growing number of therapeutic options in MM requires high-throughput combination screening tools to better allocate treatment, and facilitate personalized...

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Autores principales: Sudalagunta, Praneeth, Silva, Maria C., Canevarolo, Rafael R., Alugubelli, Raghunandan Reddy, DeAvila, Gabriel, Tungesvik, Alexandre, Perez, Lia, Gatenby, Robert, Gillies, Robert, Baz, Rachid, Meads, Mark B., Shain, Kenneth H., Silva, Ariosto S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136599/
https://www.ncbi.nlm.nih.gov/pubmed/32268267
http://dx.doi.org/10.1016/j.ebiom.2020.102716
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author Sudalagunta, Praneeth
Silva, Maria C.
Canevarolo, Rafael R.
Alugubelli, Raghunandan Reddy
DeAvila, Gabriel
Tungesvik, Alexandre
Perez, Lia
Gatenby, Robert
Gillies, Robert
Baz, Rachid
Meads, Mark B.
Shain, Kenneth H.
Silva, Ariosto S.
author_facet Sudalagunta, Praneeth
Silva, Maria C.
Canevarolo, Rafael R.
Alugubelli, Raghunandan Reddy
DeAvila, Gabriel
Tungesvik, Alexandre
Perez, Lia
Gatenby, Robert
Gillies, Robert
Baz, Rachid
Meads, Mark B.
Shain, Kenneth H.
Silva, Ariosto S.
author_sort Sudalagunta, Praneeth
collection PubMed
description BACKGROUND: Multiagent therapies, due to their ability to delay or overcome resistance, are a hallmark of treatment in multiple myeloma (MM). The growing number of therapeutic options in MM requires high-throughput combination screening tools to better allocate treatment, and facilitate personalized therapy. METHODS: A second-order drug response model was employed to fit patient-specific ex vivo responses of 203 MM patients to single-agent models. A novel pharmacodynamic model, developed to account for two-way combination effects, was tested with 130 two-drug combinations. We have demonstrated that this model is sufficiently parameterized by single-agent and fixed-ratio combination responses, by validating model estimates with ex vivo combination responses for different concentration ratios, using a checkerboard assay. This new model reconciles ex vivo observations from both Loewe and BLISS synergy models, by accounting for the dimension of time, as opposed to focusing on arbitrary time-points or drug effect. Clinical outcomes of patients were simulated by coupling patient-specific drug combination models with pharmacokinetic data. FINDINGS: Combination screening showed 1 in 5 combinations (21.43% by LD50, 18.42% by AUC) were synergistic ex vivo with statistical significance (P < 0.05), but clinical synergy was predicted for only 1 in 10 combinations (8.69%), which was attributed to the role of pharmacokinetics and dosing schedules. INTERPRETATION: The proposed framework can inform clinical decisions from ex vivo observations, thus providing a path toward personalized therapy using combination regimens. FUNDING: This research was funded by the H. Lee Moffitt Cancer Center Physical Sciences in Oncology (PSOC) Grant (1U54CA193489-01A1) and by H. Lee Moffitt Cancer Center's Team Science Grant. This work has been supported in part by the PSOC Pilot Project Award (5U54CA193489-04), the Translational Research Core Facility at the H. Lee Moffitt Cancer Center & Research Institute, an NCI-designated Comprehensive Cancer Center (P30-CA076292), the Pentecost Family Foundation, and Miles for Moffitt Foundation.
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spelling pubmed-71365992020-04-10 A pharmacodynamic model of clinical synergy in multiple myeloma Sudalagunta, Praneeth Silva, Maria C. Canevarolo, Rafael R. Alugubelli, Raghunandan Reddy DeAvila, Gabriel Tungesvik, Alexandre Perez, Lia Gatenby, Robert Gillies, Robert Baz, Rachid Meads, Mark B. Shain, Kenneth H. Silva, Ariosto S. EBioMedicine Research paper BACKGROUND: Multiagent therapies, due to their ability to delay or overcome resistance, are a hallmark of treatment in multiple myeloma (MM). The growing number of therapeutic options in MM requires high-throughput combination screening tools to better allocate treatment, and facilitate personalized therapy. METHODS: A second-order drug response model was employed to fit patient-specific ex vivo responses of 203 MM patients to single-agent models. A novel pharmacodynamic model, developed to account for two-way combination effects, was tested with 130 two-drug combinations. We have demonstrated that this model is sufficiently parameterized by single-agent and fixed-ratio combination responses, by validating model estimates with ex vivo combination responses for different concentration ratios, using a checkerboard assay. This new model reconciles ex vivo observations from both Loewe and BLISS synergy models, by accounting for the dimension of time, as opposed to focusing on arbitrary time-points or drug effect. Clinical outcomes of patients were simulated by coupling patient-specific drug combination models with pharmacokinetic data. FINDINGS: Combination screening showed 1 in 5 combinations (21.43% by LD50, 18.42% by AUC) were synergistic ex vivo with statistical significance (P < 0.05), but clinical synergy was predicted for only 1 in 10 combinations (8.69%), which was attributed to the role of pharmacokinetics and dosing schedules. INTERPRETATION: The proposed framework can inform clinical decisions from ex vivo observations, thus providing a path toward personalized therapy using combination regimens. FUNDING: This research was funded by the H. Lee Moffitt Cancer Center Physical Sciences in Oncology (PSOC) Grant (1U54CA193489-01A1) and by H. Lee Moffitt Cancer Center's Team Science Grant. This work has been supported in part by the PSOC Pilot Project Award (5U54CA193489-04), the Translational Research Core Facility at the H. Lee Moffitt Cancer Center & Research Institute, an NCI-designated Comprehensive Cancer Center (P30-CA076292), the Pentecost Family Foundation, and Miles for Moffitt Foundation. Elsevier 2020-04-05 /pmc/articles/PMC7136599/ /pubmed/32268267 http://dx.doi.org/10.1016/j.ebiom.2020.102716 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research paper
Sudalagunta, Praneeth
Silva, Maria C.
Canevarolo, Rafael R.
Alugubelli, Raghunandan Reddy
DeAvila, Gabriel
Tungesvik, Alexandre
Perez, Lia
Gatenby, Robert
Gillies, Robert
Baz, Rachid
Meads, Mark B.
Shain, Kenneth H.
Silva, Ariosto S.
A pharmacodynamic model of clinical synergy in multiple myeloma
title A pharmacodynamic model of clinical synergy in multiple myeloma
title_full A pharmacodynamic model of clinical synergy in multiple myeloma
title_fullStr A pharmacodynamic model of clinical synergy in multiple myeloma
title_full_unstemmed A pharmacodynamic model of clinical synergy in multiple myeloma
title_short A pharmacodynamic model of clinical synergy in multiple myeloma
title_sort pharmacodynamic model of clinical synergy in multiple myeloma
topic Research paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136599/
https://www.ncbi.nlm.nih.gov/pubmed/32268267
http://dx.doi.org/10.1016/j.ebiom.2020.102716
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