Proteins, Antibodies & ADCs

Explore the forefront of innovation in proteins, antibodies & ADCs through curated insights, expert perspectives, and cutting-edge technologies helping to keep you ahead of the curve.

Phage and Mammalian Display: Investigating the Filter for Developability and Machine Learning

Proteins, Antibodies & ADCs

The Four Key Principles of Integrating AI Into Biologics Discovery Workflows

Proteins, Antibodies & ADCs

Stapling for Stability: Better Multispecific scFvs

Proteins, Antibodies & ADCs

Unlocking the Secrets of Glycosylation: Enhancing Biopharmaceuticals for Better Efficacy and Safety

Proteins, Antibodies & ADCs

Using Cell Line Development for Antibodies Targeting Membrane Proteins

Proteins, Antibodies & ADCs

How Gilead Meet mAb Variety with CMC Flexibility

Proteins, Antibodies & ADCs

Antibodies to Watch: Progress in 2024 and Key Clinical Development Metrics

Proteins, Antibodies & ADCs

GSK’s Antibody Discovery for GPCR Targets

Proteins, Antibodies & ADCs

AI-Driven Revolution in Antibody Design

Proteins, Antibodies & ADCs

AI-Driven Design for Next-Gen Multi-Specific Antibodies

Proteins, Antibodies & ADCs

Designing Next-Gen Potency Assays

Proteins, Antibodies & ADCs

Formulation Design for More Stable, Less Turbid ADCs

Proteins, Antibodies & ADCs

Drugging GPCRs with a Rapid Drug Discovery Platform

Proteins, Antibodies & ADCs

Developability Assessment for Ever-More-Complex Antibody Formats

Proteins, Antibodies & ADCs

AI Models Revolutionising Antibody Structure and Sequence Design

Proteins, Antibodies & ADCs

Combining Deep Learning and Uncertainty-Aware Models to Improve Antibody Engineering

Proteins, Antibodies & ADCs

Proteins, Antibodies & ADCs

Computational Methods in Structure Based Biologics Engineering

Beating T Cell Engagers’ Toxicity Problems

Discovering Antibodies from People with Something Special

Innovative Applications of Native MS: From ADCs to AAVs

An Unconventional ADC Company Thinking About Cancer Differently

Phage and Mammalian Display: Investigating the Filter for Developability and Machine Learning

The Four Key Principles of Integrating AI Into Biologics Discovery Workflows

Stapling for Stability: Better Multispecific scFvs

Unlocking the Secrets of Glycosylation: Enhancing Biopharmaceuticals for Better Efficacy and Safety

Using Cell Line Development for Antibodies Targeting Membrane Proteins

How Gilead Meet mAb Variety with CMC Flexibility

Antibodies to Watch: Progress in 2024 and Key Clinical Development Metrics

GSK’s Antibody Discovery for GPCR Targets

AI-Driven Revolution in Antibody Design

AI-Driven Design for Next-Gen Multi-Specific Antibodies

Designing Next-Gen Potency Assays

Formulation Design for More Stable, Less Turbid ADCs

Drugging GPCRs with a Rapid Drug Discovery Platform

Developability Assessment for Ever-More-Complex Antibody Formats

AI Models Revolutionising Antibody Structure and Sequence Design

Combining Deep Learning and Uncertainty-Aware Models to Improve Antibody Engineering

ADCPedia, A Deep Learning Approach for ADC Prediction