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Clinical validation of translational antibody PBPK model using tissue distribution data generated with 89Zr-immuno-PET imaging

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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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Acknowledgements

Authors would also like to acknowledge Dr. Yvonne Jauwn from Amsterdam VUMC for her help with interpretation of PET imaging data collected from the clinic.

Funding

This research was funded by the grant from the Center for Protein Therapeutics (CPT) at the University at Buffalo. DKS is also supported by National Institute of General Medical Sciences Grant [GM114179], National Institute of Allergy and Infectious Diseases Grant [AI138195], and National Cancer Institute grants [R01CA246785 and R01CA256928].

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  1. Shufang Liu and Zhe Li have contributed equally to this work and are co-first authors.

Authors and Affiliations

  1. Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York at Buffalo, 455 Pharmacy Building, Buffalo, NY, 14214-8033, USA

    Shufang Liu, Zhe Li & Dhaval K. Shah

  2. Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands

    Marc Huisman

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  1. Shufang Liu
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Contributions

Participated in research design: ZL, SL, MH, DKS. Conducted experiments: ZL, SL. Contributed new reagents or analytic tools: ZL, SL, MH. Performed data analysis: ZL, SL, MH, DKS. Wrote or contributed to the writing of the manuscript: ZL, SL, MH, YJ, DKS.

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Correspondence to Dhaval K. Shah.

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Liu, S., Li, Z., Huisman, M. et al. Clinical validation of translational antibody PBPK model using tissue distribution data generated with 89Zr-immuno-PET imaging. J Pharmacokinet Pharmacodyn 50, 377–394 (2023). https://doi.org/10.1007/s10928-023-09869-5

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