Cambridge Healthtech Institute’s 26th Annual
Engineering Antibodies
New Strategies and Science for Engineering Next-Generation Biotherapeutics
May 13-14, 2025
The 2025 Engineering Antibodies conference will bring together leading researchers to discuss the next wave of advancements in antibody therapeutics. This track will emphasize how innovative engineering approaches are being applied to address the toughest challenges in the field, from enhancing drug stability and specificity to tackling diseases that have proven resistant to traditional therapies. With a focus on integrating new technologies, such as AI-driven design processes, this conference will offer insights into how these developments are enabling the creation of more effective, targeted treatments, marking significant progress in the realm of biologic drug development.
Coverage will include, but is not limited to:
Advances in High Throughput Screening
- Active learning loops to support rapid generation of ML training data
- High throughput functional screening methods (including agonistic selection)
- High-throughput deep sequencing of library outputs
- Integrated platforms combining HTS, structure, and sequence inputs for optimized antibody selection
Antibodies Against Membrane and Intracellular Targets
- Antibody engineering for improved cellular uptake and intracellular stability
- Engineered small protein binders for targeting membrane proteins
- Overcoming challenges in targeting GPCRs and ion channels
- Strategies for intracellular targeting, including viral vectors and alternative delivery systems
Challenging Indications with Engineering Solutions
- Antibiotic-resistant infectious diseases
- Antibody engineering for rare and orphan diseases
- Highly challenging cancers, including pancreatic, solid tumors, and brain cancers
- Neurodegenerative diseases
- New obesity treatments with improved efficacy, side effect profiles and duration of effectiveness
Improving Specificity and Mitigating Off Target Effects
- In silico design and modeling for improved specificity
- Multi-valent affinity engineering
- Optimizing affinity and specificity at the protein interfaces
- Strategies to improve chain pairing in engineered antibodies
- TCRM antibodies for improved targeting specificity
Machine Learning and AI Use Cases in Protein Engineering
- Using AI/ML to optimize and reduce candidate variants
- Developability analyses
- Expanding access to internal data
- Reimagining the experimental process for protein engineering
Panel: Near Term Challenges for AI/ML in Biotherapeutic R&D
- Benchmarking AI/ML methods compared to traditional approaches
- Development of human-relevant training data
- Expanding AI/ML prediction capabilities from molecular interactions to complex biological systems
- Extending AI/ML to genomic medicines and cell therapies
- Identifying and addressing core challenges in de novo designs
- Integrating AI/ML with existing R&D workflows
- Understanding and mitigating bias in AI/ML training datasets
The deadline for priority consideration is October 11, 2024.
All proposals are subject to review by session chairpersons and/or the Scientific Advisory Committee to ensure the overall quality of the conference program. Additionally, as per Cambridge Healthtech Institute’s policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.
Opportunities for Participation: