Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy
Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V.
The American Association for Cancer Research (AACR)
Published 2018
The American Association for Cancer Research (AACR)
Published 2018
| Publication Date: |
2018-07-17
|
|---|---|
| Publisher: |
The American Association for Cancer Research (AACR)
|
| Print ISSN: |
1078-0432
|
| Electronic ISSN: |
1557-3265
|
| Topics: |
Medicine
|
| Published by: |
| _version_ | 1836399007055740929 |
|---|---|
| autor | Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. |
| beschreibung | 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 AACR . See related commentary by Ruiz-Cerdá et al., p. 3236 |
| citation_standardnr | 6304547 |
| datenlieferant | ipn_articles |
| feed_id | 9363 |
| feed_publisher | The American Association for Cancer Research (AACR) |
| feed_publisher_url | http://www.aacr.org/ |
| insertion_date | 2018-07-17 |
| journaleissn | 1557-3265 |
| journalissn | 1078-0432 |
| publikationsjahr_anzeige | 2018 |
| publikationsjahr_facette | 2018 |
| publikationsjahr_intervall | 7984:2015-2019 |
| publikationsjahr_sort | 2018 |
| publisher | The American Association for Cancer Research (AACR) |
| quelle | Clinical Cancer Research |
| relation | http://clincancerres.aacrjournals.org/cgi/content/short/24/14/3325?rss=1 |
| search_space | articles |
| shingle_author_1 | Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. |
| shingle_author_2 | Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. |
| shingle_author_3 | Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. |
| shingle_author_4 | Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. |
| shingle_catch_all_1 | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy 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 AACR . See related commentary by Ruiz-Cerdá et al., p. 3236 Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. The American Association for Cancer Research (AACR) 1078-0432 10780432 1557-3265 15573265 |
| shingle_catch_all_2 | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy 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 AACR . See related commentary by Ruiz-Cerdá et al., p. 3236 Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. The American Association for Cancer Research (AACR) 1078-0432 10780432 1557-3265 15573265 |
| shingle_catch_all_3 | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy 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 AACR . See related commentary by Ruiz-Cerdá et al., p. 3236 Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. The American Association for Cancer Research (AACR) 1078-0432 10780432 1557-3265 15573265 |
| shingle_catch_all_4 | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy 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 AACR . See related commentary by Ruiz-Cerdá et al., p. 3236 Ribba, B., Boetsch, C., Nayak, T., Grimm, H. P., Charo, J., Evers, S., Klein, C., Tessier, J., Charoin, J. E., Phipps, A., Pisa, P., Teichgräber, V. The American Association for Cancer Research (AACR) 1078-0432 10780432 1557-3265 15573265 |
| shingle_title_1 | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy |
| shingle_title_2 | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy |
| shingle_title_3 | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy |
| shingle_title_4 | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy |
| timestamp | 2025-06-30T23:36:07.002Z |
| titel | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy |
| titel_suche | Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy |
| topic | WW-YZ |
| uid | ipn_articles_6304547 |