Inter- and intra-quartile comparison of multi-tracer PET/CT and liquid biopsy molecular markers in cancer: a futuristic perspective on evolving a "stepped care" model for individualized precision theranostics through AI/ML.

This communication provides a multidisciplinary perspective on the contribution of nuclear medicine, liquid biopsy-derived molecular markers, and AI/ML-based approaches to evolve a stepped-care model in precision oncology. The subject is of significance, particularly in the current era of precision medicine, where individualized treatment strategies increasingly require the integration of molecular imaging, molecular profiling, and multidisciplinary decision-making. The authors also emphasize the growing role of nuclear medicine in personalized treatment selection and theranostic decision-making, highlighting the next steps in molecular PET-CT imaging for further evolution of Theranostics. The past decade and a half have witnessed an exponential growth in Theranostic applications of Nuclear Medicine and its evolution as a powerful scientific precision approach, blending "diagnostics" and "therapeutics" in a simple workflow platform. One can foresee an evolution of a number of therapeutic radiopharmaceuticals in the coming years directed towards various targets on cancer cells & associated tumor microenvironment (TME) (e.g. cancer associated fibroblasts, neovascularization) and are likely to develop as preferred substitutes to systemic therapies or "sandwich" combinatorial regimens in metastatic/advanced disease, in view of their well-tolerability and relatively low toxicity. The systemic targeted treatment approaches-such as targeted chemotherapy, immune-directed treatments, and radiopharmaceutical agents-have enhanced in recent years, with a number of eligible targets traceable for the same cancer. Developing a "stepped care" precision theranostic approach-by selecting the most appropriate tumor target(s) and planning an evidence-based individualized drug-sequencing priority list on a scientific basis-is a critical need to enhance clinical outcomes by optimizing treatment efficacy with minimal toxicity. This perspective primarily emphasizes on the personalized therapy choices amongst the targeted radioligand therapy, chemotherapy, and/or immune-targeted treatments through the current and emerging molecular profiling technologies to evolve a stepped care precision theranostic model of cancer care, in an era of AI/ML.