Please use this identifier to cite or link to this item: doi:10.22028/D291-38973
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Title: A generic viral dynamic model to systematically characterize the interaction between oncolytic virus kinetics and tumor growth
Author(s): Titze, Melanie I.
Frank, Julia
Ehrhardt, Michael
Smola, Sigrun
Graf, Norbert
Lehr, Thorsten
Language: English
Title: European Journal of Pharmaceutical Sciences
Volume: 97
Pages: 38-46
Publisher/Platform: Elsevier
Year of Publication: 2017
Free key words: Mathematical model
Non-linear mixed effects modeling
Pharmacokinetic/pharmacodynamics modeling
Glioblastoma
Treatment score
DDC notations: 500 Science
610 Medicine and health
Publikation type: Journal Article
Abstract: Oncolytic viruses (OV) represent an encouraging new therapeutic concept for treatment of human cancers. OVs specifically replicate in tumor cells and initiate cell lysis whilst tumor cells act as endogenous bioreactors for virus amplification. This complex bidirectional interaction between tumor and oncolytic virus hampers the establishment of a straight dose-concentration-effect relation. We aimed to develop a generic mathematical pharmacokinetic/pharmacodynamics (PK/PD) model to characterize the relationship between tumor cell growth and kinetics of different OVs. U87 glioblastoma cell growth and titer of Newcastle disease virus (NDV), reovirus (RV) and parvovirus (PV) were systematically determined in vitro. PK/PD analyses were performed using non-linear mixed effects modeling. A viral dynamic model (VDM) with a common structure for the three different OVs was developed which simultaneously described tumor growth and virus replication. Virus specific parameters enabled a comparison of the kinetics and tumor killing efficacy of each OV. The long-term interactions of tumor cells with NDV and RV were simulated to predict tumor reoccurrence. Various treatment scenarios (single and multiple dosing with same OV, co-infection with different OVs and combination with hypothetical cytotoxic compounds) were simulated and ranked for efficacy using a newly developed treatment rating score. The developed VDM serves as flexible tool for the systematic cross-characterization of tumor-virus relationships and supports preselection of the most promising treatment regimens for follow-up in vivo analyses.
DOI of the first publication: 10.1016/j.ejps.2016.11.003
URL of the first publication: https://doi.org/10.1016/j.ejps.2016.11.003
Link to this record: urn:nbn:de:bsz:291--ds-389737
hdl:20.500.11880/35155
http://dx.doi.org/10.22028/D291-38973
ISSN: 0928-0987
Date of registration: 9-Feb-2023
Faculty: M - Medizinische Fakultät
NT - Naturwissenschaftlich- Technische Fakultät
Department: M - Infektionsmedizin
M - Pädiatrie
NT - Pharmazie
Professorship: M - Prof. Dr. Norbert Graf
M - Prof. Dr. Sigrun Smola
NT - Prof. Dr. Thorsten Lehr
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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