Cambridge Healthtech Institute’s 2nd Annual

ML/AI for Biologics Developability, Optimization, and de novo Design

Unfolding Applications and Real-World Examples

January 20-22, 2026

Computational models and methods combined with structure-based design are transforming the way antibodies and proteins are assessed for developability and optimized for development. By leveraging vast amounts of data and advanced algorithms, these models can predict key properties such as aggregation propensity, immunogenicity risk, solubility, and stability, enabling the selection of lead candidates with optimal developability profiles. De novo design is enabling the creation of entirely new biological molecules, including mini proteins and novel scaffolds. These approaches leverage computational tools and AI to design molecules with specific and novel therapeutic properties that lead to innovative and first-in-class treatments. CHI's 2nd Annual ML/AI for Biologics Developability, Optimization, and de novo Design track at the BioLogic Summit provides a platform for researchers to share cutting-edge strategies for building, validating, and applying these models. Attendees will learn about the latest advances in automated model generation, integrated multi-modal models, intuitive interfaces and design environments, and approaches for enhancing model generalizability, scalability, interpretability, and explainability. The conference will also showcase real-world examples of how these models are being used to accelerate the development of next-generation biotherapeutics, including complex modalities, ADCs, and multispecific antibodies. The paradigm shift in evaluation of drugs from animal testing to predictive preclinical models using AI is predicated on advanced computer simulations, as well as human based lab models, lab-on-a-chip, organ-on-a-chip, and closed loop systems. This meeting will showcase the integration of lab-based experimental methods with computational approaches to improve success rates in drug development.

Coverage will include, but is not limited to:

Integrated models that combine sequence, structure, omics, and functional data
De novo design of antibodies, novel scaffolds, and miniproteins
Developability and optimization predictive models for multispecific antibodies and complex modalities
Property prediction models: aggregation, immunogenicity, solubility, stability
Strategies for early-stage liability prediction
Lab-based validation and benchmarking of developability and optimization modalities

We are also seeking facilitators to lead interactive elements in addition to the podium presentations.

The deadline for priority consideration is July 11, 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: