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Computational Analysis of Cytokine Release Following Bispecific T-Cell Engager Therapy: Applications of a Logic-Based Model.
Selvaggio, Gianluca; Parolo, Silvia; Bora, Pranami; Leonardelli, Lorena; Harrold, John; Mehta, Khamir; Rock, Dan A; Marchetti, Luca.
Afiliación
  • Selvaggio G; Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
  • Parolo S; Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
  • Bora P; Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
  • Leonardelli L; Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
  • Harrold J; Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, CA, United States.
  • Mehta K; Quantitative Pharmacology & Disposition, Seattle Genetics, San Francisco, CA, United States.
  • Rock DA; Clinical Pharmacology, Modeling and Simulation, Amgen Inc., South San Francisco, CA, United States.
  • Marchetti L; Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, CA, United States.
Front Oncol ; 12: 818641, 2022.
Article en En | MEDLINE | ID: mdl-35350575
ABSTRACT
Bispecific T-cell engaging therapies harness the immune system to elicit an effective anticancer response. Modulating the immune activation avoiding potential adverse effects such as cytokine release syndrome (CRS) is a critical aspect to realizing the full potential of this therapy. The use of suitable exogenous intervention strategies to mitigate the CRS risk without compromising the antitumoral capability of bispecific antibody treatment is crucial. To this end, computational approaches can be instrumental to systematically exploring the effects of combining bispecific antibodies with CRS intervention strategies. Here, we employ a logical model to describe the action of bispecific antibodies and the complex interplay of various immune system components and use it to perform simulation experiments to improve the understanding of the factors affecting CRS. We performed a sensitivity analysis to identify the comedications that could ameliorate CRS without impairing tumor clearance. Our results agree with publicly available experimental data suggesting anti-TNF and anti-IL6 as possible co-treatments. Furthermore, we suggest anti-IFNγ as a suitable candidate for clinical studies.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article