Optimisation & Developability

Cambridge Healthtech Institute’s 16th Annual Optimisation & Developability conference presents advanced methodologies for developing and optimising therapeutic biologics for clinical success. Sessions covered include machine learning, sequence-based and in silico approaches for developability assessment, AI-driven optimisation of antibody properties, computational and experimental strategies for improved pharmacokinetics and immunogenicity risk assessment etc. Learn how to combine the myriad approaches from experimental to AI, to revolutionise the way we assess and select candidates for clinical development, and to prevent late-stage failures.

• Display of Biologics
• Engineering Antibodies
• Machine Learning Part 2

• Antibody-Based Therapies
• Emerging Targets
• Membrane Protein Targets

• Safety & Efficacy
• Advancing Multispecifics
• Engineering Bispecifics

• Immunoengineering
• Innovative CAR Therapy
• Next-Gen Immunotherapies

• Optimisation & Developability
• Analytical Characterisation
• Protein Stability & Formulation

• Leveraging Data Science
• Optimising Expression
• Developing Workflows

• Intro to Machine Learning
• Machine Learning Part 1
• Machine Learning Part 2

• Antibody-Based Therapies
• Engineering ADCs
• Next-Gen Immunotherapies

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