Early stage developability assessment is now a widely-used tool for companies to screen for desirable candidates to move forward. It starts with getting the right cell lines, designing the right screening parameters and techniques to predict the molecules’ aggregation propensity, solubility and stability, then coupled with optimisation strategies to engineer and design the desired properties. Today, the field of developability and optimization takes a step toward digitalization, where scientists are starting to apply machine learning, microfluidics and deep learning approaches to assess developability and manufacturabilty.
The 10th Annual Optimisation & Developability conference at PEGS Europe invites scientists to share their innovative approaches, methods and models they use for candidate selection and optimization.
Coverage will include, but is not limited to:
- Optimising Antibody Affinity and Specificity
- Experimental vs in silico methods
- Designing aggregation-resistant antibodies
- Engineering to improve half-life, effector functions, solubility, viscosity and stability
- Control of glycosylation and resolving sequence liability
- Balancing developability and manufacturability
- Developability Screening for Complex Molecules (Bispecifics, Multispecifics, Fusions, Conjugates, Mixtures)
- Assess aggregation propensity, self-association, protein folding
- Predict solubility, PK profiles and stability
- Methods and Models for Developability Assessment
- Biochemical and biophysical assays to determine critical attributes in early development
- Machine learning/computational approaches to assess developability and optimize molecules
- High throughput methods utilizing low sample consumption
- Miniaturization and automation techniques
- Developing predictive models around developability parameters
- Immunogenicity Risk Prediction and Assessment
* The program is subject to change without notice, due to unforeseen reason.