Conference Day Two | Thursday, October 16
For more information, download the event guide.
8:00 am Coffee & Light Breakfast
8:50 am Chair’s Opening Remarks
Moving De Novo Design for Biologics Beyond Concepts to Real-World Impact
9:00 am Comparing Structure-Based & Sequence-Based De Novo Design to Improve Precision & Scalability
Synopsis
- Contrast the strengths of structure-based design (precision, epitope targeting) with the speed and scalability of sequence-based approaches
- Examine case studies highlighting how each approach performs across antigen diversity and design complexity
- Identify hybrid strategies that combine both approaches to balance early exploration with therapeutic relevance
NEW COMPANY!
9:30 am Design of Multifunctional Molecules Using Miniprotein Building Blocks
Synopsis
- Address how de novo design enables creation of custom proteins to match specific drug development design goals
- Highlighting the use of machine learning and AI tools to design novel mini proteins with affinity, stability and specificity as key success criteria
- Discussing the development of multispecific compounds capable of engaging multiple targets within a single molecule to enhance efficacy and specificity
NEW COMPANY!
10:00 am Defining and Benchmarking De Novo Design to Build Trust & Reproducibility
Synopsis
- Tackle the lack of consensus on what constitutes “de novo design” — from novel scaffolds to full sequence generation
- Discuss the industry’s skepticism toward early success stories and explore solutions to mitigate data bias and reproducibility concerns
- Propose benchmarking strategies to validate generative pipelines and support reliable progression into experimental testing
10:30 am Morning Break & Networking
Improving Predictions of Biophysical & Developability Properties to Identify Truly Developable Candidates
11:00 am Building Better Predictive Models of Antibody & NANOBODY®–Antigen Complexes’
Synopsis
- Improve structural accuracy to guide rational antibody and NANOBODY® design
- Enhance binding prediction models to accelerate candidate screening
- Reduce experimental burden through more reliable in silico complex modeling
NEW COMPANY!
11:30 am Identification of VHH-binders From an Immunized-Antibody Repertoire Using Computational Methods
Synopsis
- Improved early antibody selection with structure-informed screening
- In silico strategy yielded a 50-60% hit rate in identifying antigen-specific binders in two different cases
- High-affinity inhibitors can be found without experimental screening
NEW COMPANY!
12:00 pm Integrating Biophysical & Biological Property Predictions to Enhance Biologic Developability
Synopsis
- Highlight the need for computational tools that predict not only biophysical properties (e.g., aggregation, viscosity, stability) but also biological behavior (e.g., receptor binding, efficacy)
- Address the current limitations of experimental methods in predicting the full therapeutic potential of biologics and the role of computational models in overcoming these challenges
- Discuss innovative approaches to integrate structural insights with biological functionality predictions to improve decision-making early in the drug development process
NEW COMPANY!
12:30 pm Lunch Break & Networking
1:30 pm Building Trust in In Silico Developability Predictions: Lessons from AstraZeneca’s “Inside” Platform
Synopsis
- Enable faster, earlier developability assessments with a platform designed for real-world protein engineering workflows
- Boost confidence and adoption by incorporating transparency, interpretability, and usability into predictive tools
- Minimize costly late-stage failures through integrated in silico insights that inform better molecule selection decisions
NEW COMPANY!
2:00 pm Advancing Biologic Developability Predictions to Enhance Drug Design & Accelerate Time-to-Market
Synopsis
- Explore innovative computational approaches to predict developability properties such as aggregation, solubility, and stability for biologic molecules, including peptides, antibodies, and conjugates
- Examine the integration of early-stage predictive models with experimental data to minimize costly trial-and-error during drug development, ultimately accelerating the timeline
- Discuss the potential of using AI/ML to forecast biologic behavior in preclinical stages, improving the likelihood of clinical success and reducing expensive late-stage failures
2:30 pm Roundtable Discussion: A Decade of Progress: Reflecting on 10 Years of Computational Drug Development for Biologics
Synopsis
- Unpack the key scientific and technological breakthroughs that have shaped the past decade of computational drug development for biologics
- Share lessons learned from industry adoption of in silico tools, from early skepticism to widespread integration in pipelines
- Explore where the field is heading – what unsolved challenges remain and what’s needed to reach the next frontier in CDD