Antigen escape is the dominant mechanism of therapeutic failure in chimeric antigen receptor (CAR) T cell and NK cell therapy, occurring in 30-60% of patients treated with single-target constructs. Existing discovery pipelines select epitopes and binders primarily on affinity metrics, neglecting evolutionary pressures that drive antigen editing, downregulation, isoform shifts, and glycosylation remodelling under sustained immunological selection. Here we describe Discovery 4.0, a five-layer computational engine developed at Pioneera Biosciences that encodes antigen escape resistance as a first-class engineering objective. Applied to four clinically validated hematologic antigens-CD19, CD20, CD22, and BCMA-Discovery 4.0 screened 20,000 synthetic binders in silico, designed 300+ CAR constructs, and validated ~100 in co-incubation assays. The leading tri-specific construct achieved a 98.1% reduction in antigen escape relative to the best monospecific control, with an effective escape probability of 0.09%. Discovery 4.0 provides a generalizable, platform-scale framework for escape-resistant immunotherapy design applicable across oncological and autoimmune indications.
Daneshvar, A., Sharifnia, M., Mashayekhi, R.
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