A new high-throughput screening framework called qCAGEs simultaneously measures α-L-fucosidase (4ME) enzymatic activity—a senescence-associated biomarker—alongside cell viability in human dermal fibroblasts. By plotting these two parameters against a baseline reference line (CARL), the system classifies compounds into four mechanistically distinct phenotypic categories: anti-aging-like, pro-aging-like, senolytic-like, and cytotoxic. The 4ME-to-cell-count ratio distinguished senescent from young cells by more than sixfold, with assay coefficient of variation below 15%, meeting rigorous high-throughput screening quality thresholds. The platform also translated successfully to 3D micropillar plate formats, with over 75% of compounds showing cosine similarity above 0.5 between 2D and 3D results.
The deeper significance here is methodological but consequential. The senolytics field has long suffered from a reproducibility problem: compounds flagged as senolytic in one assay often turn out to be generically cytotoxic in another. Single-parameter screens cannot resolve this ambiguity, which has contributed to costly failures in translating promising candidates. By anchoring phenotypic classification to a quantitative index (qCAI) rather than a binary threshold, qCAGEs creates a continuous, comparable readout across labs and compound classes. The 3D compatibility is particularly noteworthy, as tissue-mimetic formats are increasingly required before in vivo investment. Limitations remain—validation here relies solely on dermal fibroblasts, and whether 4ME faithfully tracks senescence across all tissue types is unresolved. Still, this represents a genuinely useful infrastructure advance for senolytic and geroprotective drug discovery pipelines.