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PET-based compartmental modeling of (124)I-A33 antibody: quantitative characterization of patient-specific tumor targeting in colorectal cancer. |
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| DOI |
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10.1007/s00259-015-3061-2 |
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| Abstract |
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The molecular specificity of monoclonal antibodies (mAbs) directed against tumor antigens has proven effective for targeted therapy of human cancers, as shown by a growing list of successful antibody-based drug products. We describe a novel, nonlinear compartmental model using PET-derived data to determine the "best-fit" parameters and model-derived quantities for optimizing biodistribution of intravenously injected (124)I-labeled antitumor antibodies. As an example of this paradigm, quantitative image and kinetic analyses of anti-A33 humanized mAb (also known as "A33") were performed in 11 colorectal cancer patients. Serial whole-body PET scans of (124)I-labeled A33 and blood samples were acquired and the resulting tissue time-activity data for each patient were fit to a nonlinear compartmental model using the SAAM II computer code. Excellent agreement was observed between fitted and measured parameters of tumor uptake, "off-target" uptake in bowel mucosa, blood clearance, tumor antigen levels, and percent antigen occupancy. This approach should be generally applicable to antibody-antigen systems in human tumors for which the masses of antigen-expressing tumor and of normal tissues can be estimated and for which antibody kinetics can be measured with PET. Ultimately, based on each patient's resulting "best-fit" nonlinear model, a patient-specific optimum mAb dose (in micromoles, for example) may be derived. |
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| Citation |
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European journal of nuclear medicine and molecular imaging 2015; 42(11): 1700-1706 |
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European journal of nuclear medicine and molecular imaging |
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