AI based Antibody Therapeutics Developability Assessment and Its Engineering

Learn from an informative webinar about how AI-based platforms can facilitate the development process for antibody therapeutics and ensure candidates are not only therapeutically effective but also viable for large-scale production and clinical use.
Monoclonal antibodies (mAbs) have become essential in treating a wide spectrum of diseases, with over 100 therapeutic antibody products now approved and commercially available. Although mAbs represent the fastest-growing sector in therapeutics, their development is complex, with developability being a crucial consideration. Developability evaluates the potential of an antibody candidate to be produced as a safe and effective drug.
In the context of Contract Research and Manufacturing Organizations (CRMOs), the developability assessment focuses on ensuring that an antibody candidate can progress through the chemistry, manufacturing and control (CMC) processes efficiently, affordably and within an acceptable timeframe.
It is important to examine and refine the properties related to developability early on, ideally during the discovery phase, to reduce the chances of advancing an antibody with limited developability to the CMC stage. Artificial intelligence (AI) is transforming bioinformatics research and its applications, particularly in protein and antibody analysis. AI methods are now being employed to improve the developability screening and optimization of antibody candidates.
In this webinar, the expert speaker will present the Immunoinformatics Comprehensive Service Platform, which leverages AI for the developability assessment of antibody therapeutics. This covers assessments of immunogenicity, viscosity, aggregation, degradation and post-translational modifications (PTMs). They will also cover antibody engineering services, including humanization, caninization, felinization and optimizing expression.
Case studies will be presented to demonstrate the capabilities in assessing developability and performing antibody engineering. The webinar will end with a Q&A session, allowing participants to delve into any specific areas of interest regarding AI in antibody development.