Circulating tumour cells for guiding antibody‒drug conjugate therapy: Role of artificial intelligence

Antibody‒drug conjugates (ADCs) represent a major advance in precision oncology, yet their effectiveness depends critically on adequate target antigen expression. Tumour heterogeneity and dynamic antigen expression during treatment pose major challenges for conventional tissue biopsies used in patient selection. Liquid biopsy components such as circulating tumour cells (CTCs) enable real-time, minimally invasive monitoring of tumour burden, molecular characteristics and target antigen status. This review evaluates the potential of CTC analysis to overcome the key challenges in ADC therapy, including real-time target profiling, enhanced patient stratification and longitudinal monitoring of treatment response. While acknowledging that direct clinical evidence for CTC-guided ADC selection remains limited and prospective validation is still needed, we integrate clinical evidence from CTC-guided trials across different cancer types and propose pragmatic decision-making frameworks to incorporate CTC testing into ADC treatment strategies. We also examine how artificial intelligence (AI) has improved CTC detection accuracy and discuss exploratory AI models for multi-omics integration and hypothetical AI-guided ADC recommendation systems, clearly distinguishing these by their current level of clinical evidence. Liquid biopsy-guided ADC selection has the potential to enable more personalised cancer treatment as CTC technologies advance and standardisation improves.