Engineering Biologics with Novel Functionalities and Mechanisms of Action

The PEGS Boston Engineering Stream brings together leaders in protein engineering to highlight novel discovery platforms and their application, precision targeting and conditional activation, and the increasing role of machine learning and AI in discovery and engineering. Leading industry and academic researchers join this stream every year at PEGS Boston to stay current on the most important advances in this dynamic field.

Conferences Include:

May 12-13

Display of Biologics

May 13-14

Engineering Antibodies

May 15-16

Machine Learning Approaches for Protein Engineering

Keynote and Featured Speakers:

The History of in vitro Antibody Discovery
James D. Marks, MD, PhD

Spatiotemporal Programming of Cytokine Immunotherapy for Cancer
K. Dane Wittrup, PhD, C.P. Dubbs Professor, Chemical Engineering & Bioengineering, Massachusetts Institute of Technology

Generative AI to Accelerate Prediction and Design in Biomedicine and Sustainability
Debora S. Marks, PhD, Associate Professor, Systems Biology, Harvard Medical School

2025 PROGRAMS

View By:

• Display of Biologics
• Engineering Antibodies
• Machine Learning for Protein Engineering

• Antibodies for Cancer Therapy
• Emerging Targets for Oncology & Beyond
• Driving Clinical Success in Antibody-Drug Conjugates

• TS: Intro to Multispecific Antibodies
• Advancing Multispecific Antibodies
• Engineering Bispecific and Multifunctional Antibodies

• Advances in Immunotherapy
• Engineering Cell Therapies
• Next-Generation Immunotherapies

• Difficult-to-Express Proteins
• Optimizing Protein Expression
• Maximizing Protein Production Workflows

• ML and Digital Integration in Biotherapeutic Analytics
• Biophysical Methods
• Characterization for Novel Biotherapeutics

• TS: Intro to Immunogenicity
• Predicting Immunogenicity with AI/ML Tools
• TS: Bioassay Development and Analysis

• Biologics for Immunology Indications
• Radiopharmaceutical Therapies
• Next-Generation Immunotherapies

• ML and Digital Integration in Biotherapeutic Analytics
• Predicting Immunogenicity with AI/ML Tools
• Machine Learning for Protein Engineering