Automating stochastic antibody–drug conjugation: a self-driving lab approach for enhanced therapeutic development

Abstract

Antibody–drug conjugates (ADCs) have become a promising cancer treatment over the past two decades due to their on-target drug-release capabilities. However, labor-intensive manual conjugations currently limit the throughput of ADC synthesis. Herein, we introduce a Self-Driving Lab (SDL) for automated stochastic antibody–drug conjugation and characterization. The robotic platform performs conjugations and determines drug to antibody ratios from chromatography data, enabling the production of target ADCs iteratively in a closed loop. Our SDL establishes a robust foundation for increasing ADC production throughput and accelerating the development of cancer therapeutics.