Cornell University

Memorial Sloan Kettering Cancer Center

Joseph Reginald Osborne

Neil H Bander

Steven M Larson

Shankar Vallabhajosula

Sarah M Cheal

David Ulmert

Pat B Zanzonico

Edward Komin Fung

Stanley J Goldsmith

The present disclosure describes a non-linear compartmental model using PET-derived data to predict, on a patient-specific basis, the optimal therapeutic dose of cargo carrying antibody (e.g., huA33) such as radiolabeled antibody, the antigen occupancy, residency times in normal and malignant tissues, and the cancer-to-normal tissue (e.g., colorectal cancer-to-normal colon tissue) therapeutic index. In addition, the non-linear compartmental model can be readily applied to the development of strategies such as multi-step targeting (MST) designed to further improve the therapeutic indices of RIT.

Systems and methods for determining optimum patient-specific antibody dose for tumor targeting

A method for identifying a patient for cancer therapy can include administering a diagnostic dose of a detectably labeled first binding agent to a patient, the detectably labeled binding agent being capable of binding a molecular target. The method also includes selecting a patient for administration of a therapeutic dose of a second binding agent capable of binding a cellular target, wherein the selected patient exhibits a positive reading for the detectably labeled first binding agent. Furthermore, the method can include administering a therapeutic dose of the second binding agent to the patient.

Methods and kits for diagnosis of cancer and prediction of therapeutic value

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New York, NY, United States of America

Joseph Reginald Osborne