Cambridge Healthtech Institute’s 3rd Annual
Predicting Developability and Optimization Using AI
At the Inflection Point for AI-Guided Biologics
January 20-21, 2027
Computational and structure-guided models and methods are guiding the way antibodies and proteins are assessed for developability and optimized for development. CHI’s third annual Predicting Developability and Optimization Using AI conference on January 20-21 at the third annual PEGS AI: Reinventing Biologic Development with AI-Guided Design, formerly the BioLogic Summit, will assess how well these models can predict key properties such as aggregation propensity, immunogenicity risk, solubility, and stability, enabling the early selection of lead candidates with optimal developability profiles. This conference provides a platform for researchers to share cutting-edge strategies for building, validating, and applying these models and gain valuable insight on adopting these practices in the development of drug-like molecules. Attendees will learn about the latest advances in automated model generation, integrated multi-modal models, intuitive design interfaces and environments, and approaches for enhancing model generalizability, scalability, interpretability, and explainability. Real-world examples will be showcased for how these models are being used to reinvent and vastly improve the advancement of next-generation biologics, including complex modalities, next-generation conjugates, conditionally activated and logic-gated molecules, as well as multispecific and multi-valent antibodies. This conference will highlight the stunning transformation and enormous investment that has been made in the use of AI throughout the biologic development pipeline to improve success rates and reinvent in drug development.
Coverage will include, but is not limited to:
- Designing and optimizing conditional activation with AI for pH- and ion-modulated antibodies
- Introducing integrated and generalizable models that combine sequence, structure, omics, and functional data
- Developability and optimization predictive models for multispecific antibodies and complex modalities
- Employing property prediction models to determine aggregation, immunogenicity, solubility, and stability
- Creating strategies for early-stage liability prediction
- Implementing lab-based validation and benchmarking of developability and optimization models
We are also seeking instructors and facilitators to lead the sessions below (in addition to the podium presentations):
- Competitions and benchmarking
- Interactive breakout discussions
- Demonstrations
- One day training seminars
- Working groups
The deadline for priority consideration is July 3, 2026.
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: