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Laboratory of Mathematical Biology, Division of Cancer Biology and Diagnosis, National Cancer Institute
Laboratory of Applied Studies, Division of Computer Research and Technology, National Institutes of Health, Bethesda, Maryland
Correspondence: For reprints contact: Kenji Fujimori, MD, Building 10, Room 4B-56, NIH, The Laboratory of Mathematical Biology, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892.
ABSTRACT
For successful use of radiolabeled monoclonal antibodies (MAbs) for diagnosis and therapy, it is helpful to understand both global and microscopic aspects of antibody biodistribution. In this study, antibody distribution in a tumor is simulated by splicing together information on global pharmacokinetics: transport across the capillary wall, diffusive penetration through the tumor interstitial space, and antigen-antibody interaction. The geometry simulated corresponds to spherical nodules of densely packed tumor cells. This modeling analysis demonstrates that: 1) antigen-antibody binding in tumors can retard antibody percolation; 2) high antibody affinity at a given dose tends to decrease antibody percolation because there are fewer free antibody molecules. The result is a more heterogeneous distribution; 3) the average antibody concentration in the tumor does not increase linearly with affinity; and 4) increasing antibody dose leads to better percolation and more uniform distribution. This mathematical model and the general principles developed here can be applied as well to other biologic ligands.
FOOTNOTES
* Permanent address: Department of Nuclear Medicine, School of Medicine, Hokkaido University, Sapporo, Japan.
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