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.
本公开内容描述了一种非线性区室模型,该模型使用 PET 衍生数据,根据患者特异性预测携带
抗体(如 huA33)(如放射性标记
抗体)的货物的最佳治疗剂量、抗原占位、在正常组织和恶性组织中的驻留时间以及癌症对正常组织(如结直肠癌对正常结肠组织)的治疗指数。此外,非线性区室模型还可随时应用于多步靶向(
MST)等策略的开发,旨在进一步提高 RIT 的治疗指数。