Clinical validation of translational antibody PBPK model using tissue distribution data generated with 89Zr-immuno-PET imaging.
J Pharmacokinet Pharmacodyn
; 50(5): 377-394, 2023 10.
Article
em En
| MEDLINE
| ID: mdl-37382712
ABSTRACT
The main objective of this manuscript was to validate the ability of the monoclonal antibody physiologically-based pharmacokinetic (PBPK) model to predict tissue concentrations of antibodies in the human. To accomplish this goal, preclinical and clinical tissue distribution and positron emission tomography imaging data generated using zirconium-89 (89Zr) labeled antibodies were obtained from the literature. First, our previously published translational PBPK model for antibodies was expanded to describe the whole-body biodistribution of 89Zr labeled antibody and the free 89Zr, as well as residualization of free 89Zr. Subsequently, the model was optimized using mouse biodistribution data, where it was observed that free 89Zr mainly residualizes in the bone and the extent of antibody distribution in certain tissues (e.g., liver and spleen) may be altered by labeling with 89Zr. The mouse PBPK model was scaled to rat, monkey, and human by simply changing the physiological parameters, and a priori simulations performed by the model were compared with the observed PK data. It was found that model predicted antibody PK in majority of the tissues in all the species superimposed over the observed data, and the model was also able to predict the PK of antibody in human tissues reasonably well. As such, the work presented here provides unprecedented evaluation of the antibody PPBK model for its ability to predict tissue PK of antibodies in the clinic. This model can be used for preclinical-to-clinical translation of antibodies and for prediction of antibody concentrations at the site-of-action in the clinic.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Tomografia por Emissão de Pósitrons
/
Anticorpos Monoclonais
Tipo de estudo:
Prognostic_studies
Limite:
Animals
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Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article