The Optimisation & Developability conference at PEGS Europe looks at innovative approaches, methods and models that scientists use to develop strategies for candidate selection and optimization. Today, the field of optimization and developability
takes a step toward digitalization, where scientists are starting to apply machine learning, deep learning and in silico approaches to assess developability and manufacturability.
MONDAY 18 NOVEMBER
Recommended Short Course*
SC3: Mutation and Selection Strategies Beyond Affinity Optimisation - LEARN MORE
SC4: Surfactants in Biotherapeutics: Can't Live with Them, Can't Live without Them - LEARN MORE
*Separate registration required.
12:00 Conference Registration (Foyer A)
13:30 Organiser’s Welcome
Mimi Langley, MBA, Senior Conference Director, Cambridge Healthtech Institute
13:35 Chairperson’s Opening Remarks
Lars Linden, PhD, Director & Head, Protein Biochemistry, Bayer Healthcare AG
13:45 KEYNOTE PRESENTATION: Developability Assessment to Enable Candidate Selection of Therapeutic Proteins
Hartmann, PhD, Head, Characterization, Formulation and Bioinformatics, Novartis Pharma AG
14:15 Developability of Hexabody®-Based IgG Antibodies: The Impact of Formulation on Colloidal and Conformational Stability
Kampen, PhD, Senior Scientist, Genmab
The HexaBody format is a novel platform for the potentiation of therapeutic antibodies by enhancement of antigen-dependent hexamer formation at the cell surface, which may drive subsequent target receptor activation or complement activation. The biophysical
characteristics and stability of HexaBody-based model compounds in different formulations will be discussed, probed by a variety of analytical techniques.
14:45 An Integrated Approach for Optimization and Developability Assessment of Peptides Intended for Multiple-Dose Pen Devices
Andreas Evers, PhD, Senior Scientist, Synthetic Molecular Design, Integrated Drug Discovery, Sanofi
Physicochemical properties of peptides need to be compatible with the manufacturing process and formulation requirements to ensure developability toward the commercial drug product. This aspect is often disregarded and only evaluated late in discovery,
imposing a high risk for delays in development, increased costs, and finally for the project in general. In the presentation, a general roadmap is proposed to optimize physicochemical properties towards developability of peptide drugs by combining
experimental and in silico profiling to provide stable peptide formulations at the end of discovery.
15:15 Probing Proteins in Small Volumes
Knowles, Professor, Department of Chemistry, University of Cambridge
Probing protein-protein interactions in small volumes using microfluidics. Measurements that are challenging on bulk scales become more accessible on microfluidic scales. In particular, the absence of convective mixing allows PPI’s to be probed
under native conditions in solution through monitoring changes in diffusivity as they interact. We show the applicability of this approach to different classes of interacting protein systems. Finally, we outline our efforts to bring this technology
to market in an easy-to-use platform.
15:45 Networking Refreshment Break (Foyer D)
16:15 Moderator’s Opening Remarks
PhD, Professor, Molecular Medicine, University College London Cancer Institute
16:20 Bispecific, Soluble TCR as the Next Therapeutic Platform
Bahija Jallal, PhD, CEO and Director of the Board,
Of the two adaptive immunity recognition motifs, only antibodies have been brought to patients. However, antibody therapeutics only recognize 10% of human proteome (surface-expressed). The other motif, T cell receptor (TCR), has potential to unlock
90% of the human proteome, but requires converting a low-affinity, specificity membrane receptor into a soluble therapeutic. IMCgp100, a soluble, TCR bispecific-targeting melanoma, is the most advanced soluble TCR therapeutic in development.
17:20 Attacking Cancer Cell Surfaceomes with Recombinant Antibodies
James A. Wells, PhD, Professor, Departments of Pharmaceutical Chemistry and Cellular & Molecular Pharmacology, University of California, San Francisco
The cell surface proteome (surfaceome) is the primary hub for cells to communicate with the outside world. Oncogenes are known to cause huge changes in cells and we find this translates to significant remodeling of the surfaceome. We generate
recombinant antibodies to detect and then attack these cells by toxifying the antibodies or recruiting immune cells to kill. I’ll discuss the technologies for surface protein analysis, an industrialized platform for rapid antibody generation
using phage display, and using these tool reagents for target validation.
18:20 Welcome Reception in the Exhibit Hall with Poster Viewing (Rio Pavilion)
19:30 End of Day
TUESDAY 19 NOVEMBER
07:45 Registration (Foyer A) and Morning Coffee (Foyer D)
08:30 Chairperson’s Remarks
Charlotte Deane, PhD, Professor of Structural Bioinformatics & Head of Department, Department of Statistics, University of Oxford
08:35 Physicochemical Predictors of Antibody Solution Behavior
Jonathan Kingsbury, PhD, Head, Developability and Preformulation, Biologics Development, Sanofi
The development of successful high-concentration biologic drugs requires that the therapeutic protein have properties amenable to achieving the target product profile. Selection of molecules that are resistant to unfavorable solution behaviors,
such as high viscosity and poor colloidal stability is enabled by developability assessment. A framework for developability is presented, which is centered on assessing the fit to the required dosage form and to the established manufacturing
platform. The measurement of molecular and dilute solution properties predictive of high concentration behaviors will be discussed within the context of the underlying solution phenomena and illustrated with examples.
09:05 Developability Assessment to Select Candidates for Clinical Development
PhD, Principal Scientist, Antibody Analytics, Roche
We have developed a highly versatile next generation biologics platform with a number of candidates in clinical development. During lead identification and optimization of candidates, we typically rank molecules based on their potential for
successful future development. Such developability assessments provide important information about potential liabilities, e.g., chemical degradation of amino acids or unfavorable CMC properties. We have recently expanded our developability
concept to systematically combine in-silico analysis, including pharmacokinetics analysis with biophysical and functional testing. In summary, this concept provides a more holistic picture of a candidate’s fitness for future development.
09:35 Problem-Solving Breakout Discussions*
TABLE 5: Developability of Biologic Drug: Current Trends, Challenges and Opportunities
Moderator: Johnathan Kingsbury, PhD, Head, Developability and Preformulation, Biologics Development, Sanofi
- Are there any methods that you're intersted in incorporating into your workflows?
- What are the biggest unmet needs in the field of developability?
- How successful have in silico approaches been in predicting liabilities?
TABLE 6: Combining Next-Gen Sequencing and Omics-based Approach for Antibody Optimisation
Moderator: Anup Arumughan, PhD, Principal Scientist, Antibody Analytics, Roche
- Large-scale B-cell receptor (BCR) repertoire profiling
- What is the impact of the data mining of Ig-seq data?
- Hype or Hope or a Game Changer in developing next generation biologics?
10:30 Coffee Break in the Exhibit Hall with Poster Viewing
11:15 Biophysical Screening of Unwanted Protein Interactions
Nikolai Lorenzen, PhD, Specialist, Biophysics and Formulation, Novo Nordisk A/S
Stickiness is a critical parameter to measure during developability assessment of antibodies, as it can lead to non-specific interactions, reversible self-association, and aggregation. I will give examples on how we at Novo Nordisk screen
for such unwanted protein interactions and how we collaborate with leading academic groups to develop new sophisticated biophysical screening assays.
11:45 Re-Examination of the Hydrophobic Effect at Antibody-Antigen Interfaces
PhD, Reader, School of Chemistry, University of Manchester
Prediction of developability requires a molecular level understanding of the behaviour of therapeutic proteins. We find that interactions at antibody CDRs challenge current empirical models for the hydrophobic effect. Improvements can be made
with introduction of shape-dependence, and this coupling of modern protein science with traditional protein engineering concepts will lead to better predictive models for the biologics community.
12:15 Get the Whole Story on Protein
Stability and Aggregation with Uncle
Kevin Lance, PhD, Product
Manager, Unchained Labs
Novel protein therapeutics mean that examining thermal stability and non-specific interactions is ever more important in choosing the best formulations for maintaining protein stability and avoiding aggregation. Uncle’s unique
combination of static light scattering, dynamic light scattering, and full-spectrum fluorescence tells the full story of your protein’s conformational and colloidal stability from one small sample.
12:45 Luncheon Presentation I: Keeping Kinetics Real: A New Level of Performance and Flexibility in Drug Discovery
Fabio Spiga, Senior Application Scientist, Application Team Leader Switzerland, Creoptix AG
13:15 Luncheon Presentation II: Choose the New Gold Standard
in Protein Stability Characterization
Peter A. Fung, PhD, NanoTemper Technologies
13:45 Dessert Break in the Exhibit Hall with Poster Viewing (Rio Pavilion)
14:15 Chairperson’s Remarks
Jim Warwicker, PhD, Reader, School of Chemistry, University of Manchester
14:20 Toward in silico Lead Discovery
PhD, Director & Head, Protein Biochemistry, Bayer Healthcare AG
- How will artificial intelligence and machine learning change and impact the way big pharma performs antibody lead discovery and optimization processes in the future?
- What is already there and what is needed on the journey to in silico drug discovery?
14:50 Deep Learning Enables Therapeutic Antibody Optimization in Mammalian Cells
MSc, PhD Candidate, Department for Biosystems Science & Engineering (D-BSSE), ETH Zurich
Deep learning, as part of a family of tools related to machine learning, is an emerging field of information and computer science that uses large data to identify complex relationships. Here, I will describe how we are moving beyond experimental
screening by applying deep learning to augment multi-parameter optimization of therapeutic antibodies in mammalian cells.
15:20 Using Structural Information to Aid in silico Therapeutic Design from Next Generation Sequencing Repertoires of Antibodies
Deane, PhD, Professor of Structural Bioinformatics & Head of Department, Department of Statistics, University of Oxford
We have built the freely available Observed Antibody Space database of over a billion antibody sequences. Using this data, I will show how predicted structural information can enrich data from next-generation sequencing experiments. In particular,
TAP, our novel therapeutic antibody profiler that provides five computational developability guidelines.
15:50 Antibody Protein Sequencing with Mass Spectrometry
Anthony Stajduhar, Business Development Manager, Rapid Novor, Inc.
Many applications in antibody engineering require the direct sequence of antibody proteins. At Rapid Novor (www.rapidnovor.com) we have developed a robust workflow and routinely sequence antibody proteins. Here we share our success stories,
examine common mistakes novices make and present our practices to ensure the correctness of every amino acid.
16:05 Affinity Maturation and Optimisation of Trastuzumab using RAMP
Richard Buick, Chief Technical Officer, Fusion Antibodies, plc.
We have used RAMP (Rational Affinity Maturation Platform) to generate an improved version of trastuzumab. The resulting antibody is >3-fold higher affinity and performs equivalently in several analytical assays with no reduction in specificity.
16:20 Refreshment Break in the Exhibit Hall with Poster Viewing (Rio Pavilion)
17:00 SELECTED POSTER PRESENTATION: Customized Glycosylation of Therapeutics via a Novel Production Platform
Herwig, PhD, Group Leader, Mass Spectrometry, LimmaTech Biologics AG
LimmaTech Biologics utilizes its glycosylation expertise to develop a novel glycoengineering platform for better therapeutics. Scouting of Kinetoplastida led to the identification of a unicellular eukaryote with surprisingly unique N-glycosylation
features. We engineered the organism to produce improved therapeutic proteins characterized by custom and homogenous N-glycosylation. Our glycoengineering platform bears the promise of cheaper and faster production. At the same time, it
avoids potentially disadvantageous features of mammalian cell production such as glycan microheterogeneity and variable site occupancy. Several proof of concept studies, including EPO and an anti-CD20 antibody, confirm the potential of
this novel glycoengineering platform. Next, we will perform mode of action studies of optimized candidate therapeutics to show advantageous glycoengineering effects.
17:15 POSTER HIGHLIGHT: TBD
17:30 Begin with Quality in Mind: Identifying CQAs from Early Stage of Product Lifecycle
Archana Shah, Investigator, Analytical and Product Characterisation, Biopharm Process Research, GlaxoSmithKline UK
Identification of Critical Quality Attributes (CQAs) is an imperative step in the development of biopharmaceuticals. The presentation will focus on strategies used to identify CQAs from Discovery stage to Marketing Application. It will
give an insight into how early developability screens could be used to get thorough understanding of the product and potential quality attributes affecting the safety and efficacy. Use of structure function studies and risk ranking tool
to assess the criticality of quality attributes will also be outlined.
18:00 Importance of Vernier Zone Residues in Antibody Engineering Approaches
Kalyoncu, PhD, Research Group Leader, Antibody Engineering Lab, Izmir Biomedicine and Genome Center, Turkey
Vernier zone residues locate in framework regions of antibodies affecting conformations of CDR loops and they are underrepresented in the literature. In this talk, an antibody engineering approach based on vernier zone has been applied to
improve biophysical characteristics of an anti-VEGF antibody fragment. According to our preliminary results, solubility and, surprisingly, affinity increased with rationally designed mutation(s) on vernier zone residues. My talk will show
one of important ways to improve certain biophysical and affinity characteristics of antibodies.
18:30 End of Optimisation & Developability