Webinar : De-Risking Therapeutic Antibody Development: Biological Tools in the Age of AI
De-Risking Therapeutic Antibody Development: Biological Tools in the Age of AI
Dr. Jacques Fieschi | MImAbs
From Functional Antibody Discovery to Smarter ADC Development
Can antibody discovery identify functionally effective candidates and predict which are most likely to succeed as antibody-drug conjugates?
Discover how early functional screening, experimental characterization, and AI-driven approaches can reduce uncertainty in therapeutic antibody development.
About the Webinar
Dr. Jacques Fieschi presents a CRO perspective on antibody discovery, engineering, and characterization, demonstrating how single-cell screening enables functional assessment from Day 1 of a project.
The first case study explores antibodies capable of blocking a tumor antigen from binding its receptor while sparing a closely related analog expressed on normal cells.
The second case study focuses on HER2 antibody-drug conjugates and the identification of early predictors of ADC activity. It shows how antibody affinity combined with internalization can predict ADC cytotoxicity, even before conjugation.
The presentation concludes with practical applications of AI in antibody development, including antibody and immunogen design, sequence-based liability prediction, and modeling of ADC behavior to reduce experimental workload and support earlier candidate-selection decisions.
Key Topics Covered
Single-Cell Antibody Screening
Early functional screening using Beacon technology.
Antibody Neutralization
Functional blocking activity and cross-reactivity assessment.
Affinity & Characterization
Relative affinity, BLI, and antibody candidate profiling.
HER2 Antibody-Drug Conjugates
ADC conjugation, MMAF payloads, and cytotoxic activity.
Internalization & ADC Prediction
Combining affinity and internalization to predict ADC performance.
AI in Antibody Development
AI-assisted design, liability prediction, and ADC modeling.