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Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy.
Ribba, Benjamin; Boetsch, Christophe; Nayak, Tapan; Grimm, Hans Peter; Charo, Jehad; Evers, Stefan; Klein, Christian; Tessier, Jean; Charoin, Jean Eric; Phipps, Alex; Pisa, Pavel; Teichgräber, Volker.
Afiliação
  • Ribba B; Pharmaceutical Sciences, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Basel, Switzerland. benjamin.ribba@roche.com.
  • Boetsch C; Pharmaceutical Sciences, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Basel, Switzerland.
  • Nayak T; Translational Imaging Science Oncology, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Basel, Switzerland.
  • Grimm HP; Pharmaceutical Sciences, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Basel, Switzerland.
  • Charo J; Translational Medicine Oncology, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Zurich, Switzerland.
  • Evers S; Translational Medicine Oncology, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Zurich, Switzerland.
  • Klein C; Discovery Oncology, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Zurich, Switzerland.
  • Tessier J; Translational Imaging Science Oncology, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Basel, Switzerland.
  • Charoin JE; Pharmaceutical Sciences, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Basel, Switzerland.
  • Phipps A; Pharmaceutical Sciences, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Welwyn, England.
  • Pisa P; Translational Medicine Oncology, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Zurich, Switzerland.
  • Teichgräber V; Translational Medicine Oncology, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Zurich, Switzerland.
Clin Cancer Res ; 24(14): 3325-3333, 2018 07 15.
Article em En | MEDLINE | ID: mdl-29463551
ABSTRACT

Purpose:

Optimal dosing is critical for immunocytokine-based cancer immunotherapy to maximize efficacy and minimize toxicity. Cergutuzumab amunaleukin (CEA-IL2v) is a novel CEA-targeted immunocytokine. We set out to develop a mathematical model to predict intratumoral CEA-IL2v concentrations following various systemic dosing intensities.Experimental

Design:

Sequential measurements of CEA-IL2v plasma concentrations in 74 patients with solid tumors were applied in a series of differential equations to devise a model that also incorporates the peripheral concentrations of IL2 receptor-positive cell populations (i.e., CD8+, CD4+, NK, and B cells), which affect tumor bioavailability of CEA-IL2v. Imaging data from a subset of 14 patients were subsequently utilized to additionally predict antibody uptake in tumor tissues.

Results:

We created a pharmacokinetic/pharmacodynamic mathematical model that incorporates the expansion of IL2R-positive target cells at multiple dose levels and different schedules of CEA-IL2v. Model-based prediction of drug levels correlated with the concentration of IL2R-positive cells in the peripheral blood of patients. The pharmacokinetic model was further refined and extended by adding a model of antibody uptake, which is based on drug dose and the biological properties of the tumor. In silico predictions of our model correlated with imaging data and demonstrated that a dose-dense schedule comprising escalating doses and shortened intervals of drug administration can improve intratumoral drug uptake and overcome consumption of CEA-IL2v by the expanding population of IL2R-positive cells.

Conclusions:

The model presented here allows simulation of individualized treatment plans for optimal dosing and scheduling of immunocytokines for anticancer immunotherapy. Clin Cancer Res; 24(14); 3325-33. ©2018 AACRSee related commentary by Ruiz-Cerdá et al., p. 3236.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Citocinas / Fatores Imunológicos / Modelos Teóricos / Neoplasias Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Citocinas / Fatores Imunológicos / Modelos Teóricos / Neoplasias Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article