2024 ARCHIVES

In-Person Interactive Discussions

Engage in in-depth discussions with industry experts and your peers about the progress, trends and challenges you face in your research! Interactive discussion groups play an integral role in networking with potential collaborators, provide an opportunity to share examples from your work, and be part of a group problem-solving endeavor.

These will take place IN-PERSON ONLY.

Wednesday, May 14: 1:40 – 2:25 PM

TABLE 1: The Impact of Artificial Intelligence (AI) on Biologics Discovery and Optimization
Moderator: Christopher R. Corbeil, PhD, Research Officer, Human Health Therapeutics, National Research Council Canada

Identifying the highest priority opportunities for AI in biologics discovery, alongside the primary blockers and risks that currently stifle progress
Strategies for enhancing data diversity, access, preparation and management to increase the accuracy of AI models
Speculating on the next significant breakthroughs that could revolutionize biologics discovery.
Assessing the impact of partnerships and collaborative projects on the advancement of AI in biologics discovery, including the hurdles these collaborations face

TABLE 2: How Model-Guided Design of Multi-Specific Modalities Can Benefit Your Immune-Oncology Program
Moderators:
Rebecca Chen, PhD, Principal Scientist, BioMedicine Design, Pfizer
Michael G. Zager, PhD, Associate Research Fellow, Discovery and Early Development, Pfizer

Designing multi-specific modalities can take significantly more time and resource than standard monoclonal antibodies, and often the project team is still left with the question whether their clinical candidate is optimal for the targets and intended pharmacology
Mechanistic and systems-level models of pharmacokinetics, target binding and resulting pharmacology (often referred to as quantitative systems pharmacology, or QSP) provides a platform that holistically integrates disparate data that are otherwise difficult to contextualize quantitatively to make critical design decisions. Data such as affinities, crosslinking rates, target expression and internalization, pharmacokinetic properties of the antibody, distribution to the site of action and downstream pharmacology can all be considered together via computational simulations.
These computational methods can lead to data-informed decisions that can significantly cut time and resource and can provide a powerful complement to structural design. For example, simulations may demonstrate that further affinity maturation of current leads will not result in increased pharmacology.
However, these models require data and take time to create. Therefore, planning for their development, including data generation, well in advance is key for them to provide impact on designs. This is one of the most significant challenges these efforts typically face.
In this breakout session, we plan to discuss the utility of these models in modality design, whether we as developers of these models are asking and answering the right questions in the eyes of the protein engineers, and openly discuss what we need to focus on to improve their usefulness.

TABLE 3: Protein Engineering of Multispecifics for Tailored immunotherapies
Moderator: Hilmar Ebersbach, PhD, SVP Antibody Development & Protein Engineering, ImmunOs Therapeutics AG

What are design principles?
What are challenges?
What is impact of IgG subclass for Fc-fusion proteins?
How to profile multispecifics?
What are developability considerations and characterization?

TABLE 4: Accelerating Preclinical Discovery and Development: Getting Your Favorite Protein Quickly and Cleanly
Moderator: David W. Wood, PhD, Professor, Chemical & Biomolecular Engineering, The Ohio State University

Deciding the best expression strategy for new proteins: shotgun or informed guess?
Balancing the best host: slow and reliable or quick and messy?
How pure is pure enough? Do we always need tags?
What happens when you just can’t get what you need out of your strategy? What next?

TABLE 5: Challenges and Advancements on AAV Drug Product Formulation Development
Moderator: Marilia Barros, PhD, Principal Scientist, Regeneron Pharmaceuticals

AAV formulation development common challenges and strategies to support long-term stability. Lessons learned from different AAV serotypes
Is it possible to develop a platform formulation that can be applied across all different AAV serotypes? Discuss novel and critical excipients, lyo vs liquid formulation
Stability-indicating and extended characterization methods to characterize AAV drug product critical quality attributes (aggregation, full-empty ratio, genome titer etc)
High-throughput and low-volume methods to support formulation screening and guide optimal formulation development

TABLE 6: Bioanalysis and Immunogenicity of mRNA Therapeutics
Moderator: Xiaobin Zhang, PhD, Principal Scientist, Takeda Pharmaceuticals

Challenge issues in the bioanalysis of mRNA therapeutics with different technologies: CE, qRT-PCR, LC-MS et al.
Impurity characterization for risk Assessment: impurity levels, criteria, and justification.
Fit-for-purpose bioanalytical approaches to meet the needs of pharmacokinetics, pharmacodynamics, and immunogenicity assessment with mRNA therapeutics
Product-related analysis to evaluate the immunological effects with mRNA therapeutics: protein expression from mRNA, infectious disease mRNA vaccine, and cancer mRNA vaccine.

Friday, May 17: 7:30 – 8:25 AM

TABLE 1: Engineering Novel Cytokine Functions through Experimental and Computational Approaches
Moderator: Jamie B. Spangler, PhD, Assistant Professor, Biomedical Engineering and Chemical & Biomolecular Engineering, Johns Hopkins University

Design parameters and objectives for cytokine engineering
Tailoring engineering strategies to various cytokine systems
Considerations for selecting the appropriate evolutionary and/or rational design strategies
Key factors in choosing a computational workflow for cytokine engineering

TABLE 2: De novo peptide sequencing: Applications and opportunities
Moderator: Timothy Patrick Jenkins, PhD, Assistant Professor & Head, Data Science, DTU Bioengineering

What tools are out there and how good are they?
What applications benefit most from de novo peptide sequencing?
What are current limitations and opportunities for further development?

TABLE 3: TRACeR: A Platform for Multimodal Antigen-Focused Targeting of MHC
Moderator: Possu Huang, PhD, Assistant Professor, Bioengineering, Stanford University

TABLE 4: R&D with the End-in-Mind
Moderator: Bjørn Voldborg, MSc, Head, National Biologics Facility, DTU Bioengineering, Technical University of Denmark

Determine what your end-product could look like
Consider the full pipeline of your candidate as early as possible
Select suitable expression systems early on
Use regulatory acceptable hosts as soon as possible

TABLE 5: Biotherapeutic Expression & Production Pipeline – Week in Review
Moderators:
Richard Altman, MS, Field Application Scientist, Life Science Solutions, Thermo Fisher Scientific
Henry C. Chiou, PhD, Senior Director General Manager, Biosciences, Thermo Fisher Scientific
Dominic Esposito, PhD, Director, Protein Sciences, Frederick National Laboratory

Highlights from the week’s presentations
New technologies and strategies
With these new technologies, how do we increase not only the efficiency and throughput of recombinant protein expression, but of the entire protein production process?
Challenges and future trends

TABLE 6: Characterization, Screening and Design of Bispecific Antibodies
Moderator: Dennis Åsberg, PhD, Project Manager, Global Research Technologies, Novo Nordisk A/S

Which specific challenges are seen when screening for developability of bispecific antibodies?
How can the characterization of the parent antibodies inform on the properties of the bispecific antibody?
How to assess and define purity of multivalent-antibody or multi-specific formats?
Can a developability profile and/or formulation stability on par with standard antibodies normally be reached for multivalent or multi-specific formats?