8:30 am Registration & Networking
9:10 am Chair’s Opening Remarks
9:15 am Developing a Suite of Coarse-Grained Molecular Models for Protein Candidate Selection
9:45 am Computational Drug Discovery Through Computational Scientific Expert Identification: Data-Driven Recruiting, Organization Building, & Virtual Biotech 2.0
10:15 am Speed Networking & Morning Networking Break
11:00 am Generative Machine Learning for Design of Peptides & Peptidomimetics
11:30 am AI-Driven Antibody Diversity to Explore Discovery & Developability
12:00 pm Networking Roundtable Lunch
Synopsis
Make the most of your lunch break by joining an informal roundtable discussion:
Applicability of Machine Learning in Biologics Discovery & Development
1:30 pm The Many-Body Physics of Antibody Formulation
2:00 pm The Real Value & Opportunities in End-to-End Computational Drug Development for Biologics
2:30 pm Fireside Chat: A Unified Approach to Biologic Drug Design, Discovery & Development
Synopsis
- What is the future opportunity with bioinformatics?
- From candidate screening to developability prediction to manufacturing
- Where are we seeing traction? Modality vs antibody vs other biologics?
- Collaboration with academia & lessons learned during COVID
- Revolutionizing biologics drug discovery and development approach – from philosophy to practicality