TY - JOUR
T1 - Quantitative Systems Pharmacology Modeling of PBMC-Humanized Mouse to Facilitate Preclinical Immuno-oncology Drug Development
AU - Ma, Huilin
AU - Pilvankar, Minu
AU - Wang, Jun
AU - Giragossian, Craig
AU - Popel, Aleksander S.
N1 - Publisher Copyright:
© 2020 American Chemical Society.
PY - 2021/2/12
Y1 - 2021/2/12
N2 - Progress in immunotherapy has resulted in explosively increased new therapeutic interventions and they have shown promising results in the treatment of cancer. Animal testing is performed to provide preliminary efficacy and safety data for drugs under development prior to clinical trials. However, translational challenges remain for preclinical studies such as study design and the relevance of animal models to humans. Hence, only a small fraction of cancer patients showed response. The explosion of drug candidates and therapies makes preclinical assessment of every plausible option impossible, but it can be easily tested using Quantitative System Pharmacology (QSP) models. Here, we developed a QSP model for humanized mice. Tumor growth dynamics, T cell dynamics, cytokine release, immune checkpoint expression, and drug administration were modeled and calibrated using experimental data. Tumor growth inhibition data were used for model validation. Pharmacokinetics of T cell engager (TCE), tumor growth profile, T cell expansion in the blood and infiltration into tumor, T cell dissemination from primary tumor, cytokine release profile, and expression of additional PD-L1 induced by IFN-γwere modeled and calibrated using a variety of experimental data and showed good consistency. Mouse-specific response to T cell engager monotherapy also showed the key features of in vivo efficacy of TCE. This novel QSP model, designed for human peripheral blood mononuclear cells (PBMC) engrafted xenograft mice, incorporating the most critical components of the mouse model with key cancer and immune cells, can become an integral part of preclinical drug development.
AB - Progress in immunotherapy has resulted in explosively increased new therapeutic interventions and they have shown promising results in the treatment of cancer. Animal testing is performed to provide preliminary efficacy and safety data for drugs under development prior to clinical trials. However, translational challenges remain for preclinical studies such as study design and the relevance of animal models to humans. Hence, only a small fraction of cancer patients showed response. The explosion of drug candidates and therapies makes preclinical assessment of every plausible option impossible, but it can be easily tested using Quantitative System Pharmacology (QSP) models. Here, we developed a QSP model for humanized mice. Tumor growth dynamics, T cell dynamics, cytokine release, immune checkpoint expression, and drug administration were modeled and calibrated using experimental data. Tumor growth inhibition data were used for model validation. Pharmacokinetics of T cell engager (TCE), tumor growth profile, T cell expansion in the blood and infiltration into tumor, T cell dissemination from primary tumor, cytokine release profile, and expression of additional PD-L1 induced by IFN-γwere modeled and calibrated using a variety of experimental data and showed good consistency. Mouse-specific response to T cell engager monotherapy also showed the key features of in vivo efficacy of TCE. This novel QSP model, designed for human peripheral blood mononuclear cells (PBMC) engrafted xenograft mice, incorporating the most critical components of the mouse model with key cancer and immune cells, can become an integral part of preclinical drug development.
KW - PBMC humanized mice
KW - computational biology
KW - immuno-oncology
KW - immunocompromised mice
KW - mathematical model
KW - patient-derived xenograft
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U2 - 10.1021/acsptsci.0c00178
DO - 10.1021/acsptsci.0c00178
M3 - Article
C2 - 33615174
AN - SCOPUS:85097829809
SN - 2575-9108
VL - 4
SP - 213
EP - 225
JO - ACS Pharmacology and Translational Science
JF - ACS Pharmacology and Translational Science
IS - 1
ER -