Abstract: The present disclosure provides compositions and methods for the detection and treatment of cancer. Specifically, the compositions of the present technology include novel DOTA-haptens that may be complexed with a radioisotope (e.g., 225Ac). Also disclosed herein are methods of the using the DOTA-haptens of the present technology in diagnostic imaging as well as pretargeted radioimmunotherapy.

Abstract: The present disclosure provides compositions and methods for the treatment of cancer. Specifically, the compositions of the present technology include novel clearing agents that may be used in pretargeted radioimmunotherapy.

Abstract: The present disclosure provides compositions and methods for the treatment of cancer. Specifically, the compositions of the present technology include novel clearing agents that may be used in pretargeted radioimmunotherapy.

Abstract: The present disclosure provides compositions and methods for the detection and treatment of cancer. Specifically, the compositions of the present technology include novel DOTA-haptens that may be complexed with a radioisotope (e.g., 225Ac). Also disclosed herein are methods of the using the DOTA-haptens of the present technology in diagnostic imaging as well as pretargeted radioimmunotherapy.

Abstract: The present disclosure relates generally to immunoglobulin-related compositions (e.g., antibodies or antigen binding fragments thereof) that can bind to and neutralize the activity of polysialic acid. The antibodies of the present technology are useful in methods for detecting and treating a polysialic acid-associated cancer in a subject in need thereof.

Abstract: 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.

Abstract: 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.

Abstract: The present invention provides compositions and methods for detecting, analyzing, and identifying biomolecules. More particularly, the invention provides Element Coded Affinity Tags comprising a metal chelate and a metal ion and methods of using the tags to detect, analyze, and identify biomolecules including polypeptides, nucleic acids, lipids, and polysaccharides.