Day One

This structured networking session provides the perfect opportunity to connect with industry frontrunners and key opinion leaders working at the interface of AI/ML and computational drug design for biologics. Establish meaningful connections to build upon at the rest of the conference.

• Optimized AI generation achieves higher hit rates, nearly tripling computational design success and drastically slashing early-stage trial-and-error costs
• Wet-lab results confirm that our AI-designed sequences successfully fold and exhibit real catalytic activity, providing validated functional enzymes
• Sequence optimization significantly boosts antibody expression, thus improving production yields and directly derisking downstream manufacturing bottlenecks

• Demonstrating that miniproteins are a powerful, stable therapeutic modality with high-affinity, specific binding
• Discussing development using a combination of de novo design, synthetic biology, and laboratory automation
• Creating a toolbox of modular miniprotein domains with ideal drug-like and developability profiles

• Discussing epitope clustering using the latest structure prediction tools
• Exploring agreement with experimental results
• Proposing a strategy on how such results could benefit labs in prioritizing candidate measurement

• Developing an end-to-end AI-MPRO platform to design miniprotein therapeutics against challenging targets, including ion channels and complex multi-protein interfaces that are difficult to address with conventional modalities
• Combining de novo protein design with rapid in silico experimental iteration, enables efficient progression from computational discovery to in vitro and in vivo preclinical proof-of-concept
• Generating compact, highly optimized miniprotein candidates with the potential to deliver first-in-class or best-in-class therapies for targets traditionally considered intractable

• Shifting from screening-based discovery towards biologics by design through AI momentum and applications
• Exploring how real impact today is accelerating design-make-test cycles and reducing experimental iteration
• Recognizing that success requires integrated AI platforms that combine generative models, predictive models, and experimental feedback

• Exploring how a de novo protein was designed to target a heterodimeric receptor in the absence of a solved structure
• Achieving biased agonism with a de novo protein
• Emphasizing the importance of a human-in-the-loop AI/ML pipeline for biologics design

• Exploring how an adversarial generation engine with continuous in silico evaluation dynamically steers de novo miniprotein design to improve multi-objective hit rates
• Discussing the use of labelled design and click chemistry–based modular assembly to enable efficient scaling from single miniproteins and VHHs to multispecific constructs
• Identifying informative labels using model heuristics to bias generative sampling towards optimized affinity, specificity, stability, and immunogenicity profiles

Connect with peers in a relaxed atmosphere and continue to forge new and existing relationships, while exploring the latest advancements at the intersection of computation and AI for biologics design.

To submit a poster, please contact: info@hansonwade.com