Real-Time Biosensing of Cancer Therapy Response: Dynamic Biomarkers and the Shift Toward Feedback-Driven Precision Oncology

Abstract

Cancer therapy response is still judged largely by tools that report late. Imaging and intermittent laboratory tests register treatment effects only once substantial structural change has accumulated, yet the molecular, metabolic, and immunological events that decide whether a therapy succeeds unfold within hours to days of the first dose. This review argues that dynamic biomarkers, monitored in real time or at high frequency by emerging biosensing platforms, supply a missing temporal axis in precision oncology. Two axes are already established: Genomics defines what to target, and imaging defines where disease resides. Biosensing defines when and how a tumor is responding. We synthesize the biological rationale for dynamic monitoring, define what “real-time” should and should not mean in oncology, and weigh the evidence for tumor-derived, metabolic, and immune biomarker sensing, separating what is clinically demonstrated (most notably circulating tumor DNA kinetics) from what remains preclinical. Rather than cataloguing devices, we organize biosensing around the biological questions it answers and the decision points it could inform, then examine four barriers to adoption (sensor stability, biomarker standardization, data interpretability, and regulatory and ethical constraints) and identify the knowledge gaps that most limit progress. The core conclusion is that real-time biosensing is best understood not as a competing modality but as the temporal complement to genomics and imaging; its adoption is constrained less by sensor novelty than by the absence of standardized thresholds and prospective, interventional evidence that acting on dynamic signals improves outcomes.