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dc.contributor.authorZanzonico, Pat-
dc.contributor.authorCarrasquillo, Jorge A-
dc.contributor.authorPandit-Taskar, Neeta-
dc.contributor.authorO'Donoghue, Joseph A-
dc.contributor.authorHumm, John L-
dc.contributor.authorSmith-Jones, Peter-
dc.contributor.authorRuan, Shutian-
dc.contributor.authorDivgi, Chaitanya-
dc.contributor.authorScott, Andrew M-
dc.contributor.authorKemeny, Nancy E-
dc.contributor.authorFong, Yuman-
dc.contributor.authorWong, Douglas-
dc.contributor.authorScheinberg, David-
dc.contributor.authorRitter, Gerd-
dc.contributor.authorJungbluth, Achem-
dc.contributor.authorOld, Lloyd J-
dc.contributor.authorLarson, Steven M-
dc.identifier.citationEuropean journal of nuclear medicine and molecular imaging 2015; 42(11): 1700-1706-
dc.description.abstractThe 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.-
dc.titlePET-based compartmental modeling of (124)I-A33 antibody: quantitative characterization of patient-specific tumor targeting in colorectal cancer.-
dc.typeJournal Article-
dc.typeResearch Support, N.I.H., Extramural-
dc.identifier.journaltitleEuropean journal of nuclear medicine and molecular imaging-
dc.identifier.affiliationLudwig Institute for Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USAen
dc.identifier.affiliationDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10021, USA-
dc.identifier.affiliationDepartment of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USAen
dc.identifier.affiliationDepartment of Surgery, City of Hope, Duarte, CA, USAen
dc.identifier.affiliationDepartment of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USAen
dc.identifier.affiliationColumbia University Medical Center, New York, NY, USAen
dc.identifier.affiliationDepartment of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USAen
dc.identifier.affiliationDepartments of Psychiatry and Radiology, Stony Brook School of Medicine, Stony Brook, NY, USAen
dc.identifier.affiliationOlivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australiaen
dc.identifier.affiliationLa Trobe University, Melbourne, Australiaen
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