PET-based compartmental modeling of 124 I-A33 antibody: quantitative characterization of patient-specific tumor targeting in colorectal cancer

Purpose 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. Methods 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. Results 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. Conclusion 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.