Cambridge Healthtech Institute’s 27th Annual
Engineering Antibodies
New Strategies and Science for Engineering Next-Generation Biotherapeutics
May 12-13, 2026
Antibody engineering continues to push past traditional limits, opening new frontiers in target selection, delivery, and design. Cambridge Healthtech Institute's 27th annual Engineering Antibodies conference brings together leaders at the cutting edge of CNS delivery, conditional activation, and small protein scaffolds to address some of the toughest challenges in biologics R&D. Sessions will delve into next-generation strategies for crossing the blood–brain barrier, improving selectivity through dual-targeting and computationally guided epitope design, and applying AI-driven scaffold evolution to minimize immunogenicity and manufacturing risks. Case studies will highlight progress with nanobodies, DARPins, intracellular antibodies, and other unconventional formats, as well as machine learning approaches for epitope discovery and liability prediction. Attendees will leave with a clearer picture of how engineering innovation is redefining what antibodies can do and where they can go.
Coverage will include, but is not limited to:
Engineering Delivery to the Brain
- Disease-specific considerations
- Dual-target and multispecific approaches
- Emerging modalities for CNS access
- Managing risk
- State of the science for crossing the BBB
Enhancing Selectivity and Specificity
- Next-generation conditional activation strategies
- Dual-target engagement and avidity
- Computationally guided epitope design for complex antigens
- Resolving gaps in off-target prediction
Progress in Developing Small Protein Scaffolds
- AI-driven scaffold design and library evolution
- Engineering to mitigate Immunogenicity and manufacturability risks
- Lessons learned from clinical development
- Matching scaffolds to biological problems
- Rational design considerations for nanobodies, DARPins, and minibinders
Challenging Targets and Pathways
- Conformation-specific and allosteric epitopes
- GPCRs, ion channels, and transporters
- HLA and peptide–MHC complexes
- Intracellular antibodies
- Targeting intrinsically disordered proteins
Machine Learning Use Cases in Protein Engineering
- Benchmarking ML vs. conventional approaches
- Epitope discovery and multi-epitope design
- Integrating AI with functional screening data
- Predicting and reducing specific developability liabilities
Panel: Near Term Challenges for AI/ML in Biotherapeutic R&D
The deadline for priority consideration is October 17, 2025.
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: