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hal.structure.identifierSimulation and Modeling of Adaptive Response for Therapeutics in Cancer [SMARTc]
dc.contributor.authorRODALLEC, Anne
hal.structure.identifierSimulation and Modeling of Adaptive Response for Therapeutics in Cancer [SMARTc]
dc.contributor.authorFANCIULLINO, Raphaelle
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorBENZEKRY, Sébastien
hal.structure.identifierSimulation and Modeling of Adaptive Response for Therapeutics in Cancer [SMARTc]
dc.contributor.authorCICCOLINI, Joseph
dc.date.accessioned2024-04-04T02:58:45Z
dc.date.available2024-04-04T02:58:45Z
dc.date.issued2019-07-01
dc.identifier.issn0250-7005
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/192683
dc.description.abstractEnAs part of the Pharmacology & Molecular Mechanisms (PAMM) Group, European Organization for Research and Treatment on Cancer (EORTC) 2019 winter Meeting Educational sessions, special focus has been placed on strategies to be undertaken to reduce the attrition rate when developing immune-oncology drugs. Immune checkpoint inhibitors have been game-changing drugs in several settings over the past decade such as melanoma and lung cancer. However, during the last years a rising number of studies failing to further improve clinical outcome in patients with cancer was recorded. Extensive pharmacometrics such as pharmacokinetics/ pharmacodynamics modeling support should help to overcome the current glass ceiling that has apparently been reached with immuno-oncology drugs (IOD). In particular, it should help in the issue of setting up combinatorial regimen (i.e. combining immune checkpoint inhibitors with cytotoxics, anti-angiogenesis or targeted therapies) that can no longer be addressed when following standard trial-and-error approaches, but rather by using mathematical-derived algorithms as decision-making tools by investigators for rational design. In routine clinical setting, developing therapeutic drug monitoring of immune checkpoint inhibitors with adaptive dosing strategies has been a long-neglected strategy. Still, substantial improvements might be achieved using dedicated tools for precision medicine and personalized medicine in immunotherapy.
dc.language.isoen
dc.publisherInternational Institute of Anticancer Research
dc.subject.enPK/PD
dc.subject.enImmuno-oncology drugs
dc.subject.enPharmacometrics
dc.subject.enCombinatorial strategies
dc.subject.enReview
dc.title.enIs There Any Room for Pharmacometrics With Immuno-Oncology Drugs? Input from the EORTC-PAMM Course on Preclinical and Early-phase Clinical Pharmacology
dc.typeArticle de revue
dc.identifier.doi10.21873/anticanres.13486
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halSciences du Vivant [q-bio]/Cancer
dc.subject.halPhysique [physics]/Physique [physics]/Analyse de données, Statistiques et Probabilités [physics.data-an]
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologie
dc.subject.halSciences du Vivant [q-bio]/Sciences pharmaceutiques/Pharmacologie
dc.subject.halStatistiques [stat]/Applications [stat.AP]
bordeaux.journalAnticancer Research
bordeaux.page3419-3422
bordeaux.volume39
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue7
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-02383831
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02383831v1
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