Conference Day One
Day One
Wednesday 25th October 2023
8:00 am Registration & Morning Coffee
8:50 am Chair’s Opening Remarks
Bridging the Data Gap with Innovative Computational Approaches
9:00 am Plenary Panel: Navigating the Recent Trends in Computational Drug Development & Their Implications in Biologics Processes
Synopsis
- Reaffirming the importance of fostering collaboration to overcome the data gap
- Assessing if insights from big tech can empower biologics decision making
- Addressing the next steps in computational approaches to improve data integrity and diversity
Session to be moderated by Maria Wendt.
9:45 am Employing Computational Tools for Initial Antibody Library Design & Optimization with Limited Data Availability
Synopsis
- Design diverse antibody libraries enriched in binding sequences using classical computational and deep learning approaches
- Further optimize library design by training machine learning methods on small datasets
10:15 am Morning Break & Speed Networking
Synopsis
As the CDD for Biologics community is reunited, this valuable session will ensure you get the chance to reconnect with peers and make brand new connections too! This structured networking opportunity will pair you with fellow attendees for several 3-minute introductions, ensuring you have the opportunity to meet and network with your academic and industry colleagues!
11:15 am Benchmarking Computational Approaches to Support Biologics Discovery
Synopsis
- Integrating computational approaches with experimental workflows to support data validation
- Exploring the rationale to establish a baseline that balances computational and experimental approaches
- Discovering the potential for this approach to empower biologics discovery and development
Predictability For Biologics Discovery
12:00 pm Breakout Roundtable Discussions: Exploring the Success of Computational Models Across Pipelines
Synopsis
This session is your opportunity to share your most pressing challenges, and work as a group to come up with solutions that you can implement right away! Each topic area will have several small groups, and each group will have 20 minutes to discuss ways to overcome barriers in implementing computational models across pipelines. Groups will then share their findings with all attendees, giving you maximum exposure to new ideas!
12:00 pm Breakout Roundtable Discussions: Exploring the Success of Computational Models Across Pipelines
Synopsis
This session is your opportunity to share your most pressing challenges, and work as a group to come up with solutions that you can implement right away! Each topic area will have several small groups, and each group will have 20 minutes to discuss ways to overcome barriers in implementing computational models across pipelines. Groups will then share their findings with all attendees, giving you maximum exposure to new ideas!
1. Predictive Model Development:
Synopsis
- Reaffirming and understanding the success and challenges in developing predictive models
- Uncovering recommendations of next steps to achieve this
2. Error Reduction:
Synopsis
- Strategizing methods to reduce errors and overcome computational limitations
- Uncovering recommendations of next steps to achieve this
3. Validating in silico tools:
Synopsis
- Developing practical methods to establish validated in silico tools to set a gold standard
- Uncovering recommendations of next steps to achieve this
12:30 pm Lunch Break
1:30 pm Towards Biologics by Design: Computational Optimization of Multi-Specific Protein Therapeutics
Synopsis
- The generation of multi-specific protein therapeutics necessitates the exploration of extensive design spaces, a task that cannot be entirely covered through wet lab experiments alone
- By harnessing our systematically collected and curated data assets, we have developed computational and machine learning-based optimization workflows for predicting molecular properties such as expression, activity, stability, and clearance
- We will showcase examples of how our computational pipeline assists in navigating through the vast design space of multi-specific biologics
2:00 pm OmniDeepTM: An adaptive scalable deep learning platform that harnesses insights from diverse OmniAb(R) antibody repertoires
Synopsis
- OmniDeep is a suite of in silico tools for therapeutic discovery and optimization that are woven throughout OmniAb’s various technologies and capabilities
- These tools include structural modeling, molecular dynamics simulations, large multi-species antibody databases, and an adaptive and scalable deep learning platform
- It uses unbiased data-driven organization/clustering techniques and active learning paradigms to gain deeper insights of the vast antibody repertoires generated, which helps our partners better harnesses the Biological Intelligence™ of our optimized animal species
2:15 pm Target Selection to Maximize Success from Your Antibody Platform
Synopsis
- Analyzing the importance of target selection and optimization
- Discover “validated” targets that leverage your platform’s competitive advantage
- Address the value and challenges of machine learning and AI for target selection
2:45 pm Networking Break & Poster Session
Synopsis
Witness some of the latest and greatest research in the computational space by drug developers, academics, and researchers in this spotlight poster session.
Predictability For Biologics Developability
3:30 pm Leveraging Machine Learning & Physical Chemistry to Design High Potency Molecules From Next-Generation Sequencing of Screening Outputs
Synopsis
- Understanding the current challenge in library design that needs to be overcome
- Spotlighting the rationale behind this process
- Uncovering the future hopes for this process
4:00 pm Combining Molecular Modeling and Machine Learning to Predict Concentrated Antibody Solution
Synopsis
- Identify molecular descriptors to predict antibody viscosity
- Develop fast screening tool using deep learning
- Strategies to overcome the variations in viscosity and aggregation as the formulation changes