Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
01 2020
Historique:
received: 26 06 2019
accepted: 21 11 2019
revised: 06 02 2020
pubmed: 28 1 2020
medline: 9 4 2020
entrez: 28 1 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 31986133
doi: 10.1371/journal.pcbi.1007218
pii: PCOMPBIOL-D-19-01041
pmc: PMC7004559
doi:

Substances chimiques

Antineoplastic Agents 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1007218

Subventions

Organisme : Medical Research Council
Pays : United Kingdom

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Roger J W Hill (RJW)

EPSRC & MRC Centre for Doctoral Training in Mathematics for Real-World Systems, University of Warwick, Coventry, UK.

Pasquale F Innominato (PF)

North Wales Cancer Centre, Ysbyty Gwynedd, Betsi Cadwaladr University Health Board, Bangor, UK.
Cancer Chronotherapy Team, Cancer Research Centre, Division of Biomedical Sciences, Warwick Medical School, Coventry, UK.

Francis Lévi (F)

Cancer Chronotherapy Team, Cancer Research Centre, Division of Biomedical Sciences, Warwick Medical School, Coventry, UK.
INSERM and Paris Sud university, UMRS 935, Team "Cancer Chronotherapy and Postoperative Liver Functions", Campus CNRS, Villejuif, F-94807, France. & Honorary position, University of Warwick, UK.

Annabelle Ballesta (A)

INSERM and Paris Sud university, UMRS 935, Team "Cancer Chronotherapy and Postoperative Liver Functions", Campus CNRS, Villejuif, F-94807, France. & Honorary position, University of Warwick, UK.

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