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Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy
Precision medicine requires accurate technologies for drug administration and proper systems pharmacology approaches for patient data analysis. Here, plasma pharmacokinetics (PK) data of the OPTILIV trial in which cancer patients received oxaliplatin, 5-fluorouracil and irinotecan via chronomodulate...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004559/ https://www.ncbi.nlm.nih.gov/pubmed/31986133 http://dx.doi.org/10.1371/journal.pcbi.1007218 |
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author | Hill, Roger J. W. Innominato, Pasquale F. Lévi, Francis Ballesta, Annabelle |
author_facet | Hill, Roger J. W. Innominato, Pasquale F. Lévi, Francis Ballesta, Annabelle |
author_sort | Hill, Roger J. W. |
collection | PubMed |
description | Precision medicine requires accurate technologies for drug administration and proper systems pharmacology approaches for patient data analysis. Here, plasma pharmacokinetics (PK) data of the OPTILIV trial in which cancer patients received oxaliplatin, 5-fluorouracil and irinotecan via chronomodulated schedules delivered by an infusion pump into the hepatic artery were mathematically investigated. A pump-to-patient model was designed in order to accurately represent the drug solution dynamics from the pump to the patient blood. It was connected to semi-mechanistic PK models to analyse inter-patient variability in PK parameters. Large time delays of up to 1h41 between the actual pump start and the time of drug detection in patient blood was predicted by the model and confirmed by PK data. Sudden delivery spike in the patient artery due to glucose rinse after drug administration accounted for up to 10.7% of the total drug dose. New model-guided delivery profiles were designed to precisely lead to the drug exposure intended by clinicians. Next, the complete mathematical framework achieved a very good fit to individual time-concentration PK profiles and concluded that inter-subject differences in PK parameters was the lowest for irinotecan, intermediate for oxaliplatin and the largest for 5-fluorouracil. Clustering patients according to their PK parameter values revealed patient subgroups for each drug in which inter-patient variability was largely decreased compared to that in the total population. This study provides a complete mathematical framework to optimize drug infusion pumps and inform on inter-patient PK variability, a step towards precise and personalized cancer chronotherapy. |
format | Online Article Text |
id | pubmed-7004559 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-70045592020-02-19 Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy Hill, Roger J. W. Innominato, Pasquale F. Lévi, Francis Ballesta, Annabelle PLoS Comput Biol Research Article Precision medicine requires accurate technologies for drug administration and proper systems pharmacology approaches for patient data analysis. Here, plasma pharmacokinetics (PK) data of the OPTILIV trial in which cancer patients received oxaliplatin, 5-fluorouracil and irinotecan via chronomodulated schedules delivered by an infusion pump into the hepatic artery were mathematically investigated. A pump-to-patient model was designed in order to accurately represent the drug solution dynamics from the pump to the patient blood. It was connected to semi-mechanistic PK models to analyse inter-patient variability in PK parameters. Large time delays of up to 1h41 between the actual pump start and the time of drug detection in patient blood was predicted by the model and confirmed by PK data. Sudden delivery spike in the patient artery due to glucose rinse after drug administration accounted for up to 10.7% of the total drug dose. New model-guided delivery profiles were designed to precisely lead to the drug exposure intended by clinicians. Next, the complete mathematical framework achieved a very good fit to individual time-concentration PK profiles and concluded that inter-subject differences in PK parameters was the lowest for irinotecan, intermediate for oxaliplatin and the largest for 5-fluorouracil. Clustering patients according to their PK parameter values revealed patient subgroups for each drug in which inter-patient variability was largely decreased compared to that in the total population. This study provides a complete mathematical framework to optimize drug infusion pumps and inform on inter-patient PK variability, a step towards precise and personalized cancer chronotherapy. Public Library of Science 2020-01-27 /pmc/articles/PMC7004559/ /pubmed/31986133 http://dx.doi.org/10.1371/journal.pcbi.1007218 Text en © 2020 Hill et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hill, Roger J. W. Innominato, Pasquale F. Lévi, Francis Ballesta, Annabelle Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy |
title | Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy |
title_full | Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy |
title_fullStr | Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy |
title_full_unstemmed | Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy |
title_short | Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy |
title_sort | optimizing circadian drug infusion schedules towards personalized cancer chronotherapy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004559/ https://www.ncbi.nlm.nih.gov/pubmed/31986133 http://dx.doi.org/10.1371/journal.pcbi.1007218 |
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