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Related Experiment Video

Updated: Dec 25, 2025

Single-cell Screening Method for the Selection and Recovery of Antibodies with Desired Specificities from Enriched Human Memory B Cell Populations

Single-cell Screening Method for the Selection and Recovery of Antibodies with Desired Specificities from Enriched Human Memory B Cell Populations

Published on: August 22, 2019

Predicting Antibody Developability Profiles Through Early Stage Discovery Screening.

Marc Bailly¹, Carl Mieczkowski¹, Veronica Juan¹

¹Discovery Biologics, Protein Sciences, South San Francisco, CA, USA.

|April 7, 2020

Summary

This summary is machine-generated.

A high-throughput developability workflow assesses physicochemical properties of monoclonal antibodies early in drug development. This process efficiently selects optimal antibody candidates, streamlining the CMC phase and enabling timely engineering.

Keywords:

CMC Monoclonal antibodies antibody discovery antibody screening biophysical properties developability manufacturability protein analytics protein engineering

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Last Updated: Dec 25, 2025

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Published on: August 22, 2019

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A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

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Published on: March 25, 2014

Area of Science:

Biopharmaceutical development
Protein engineering
Drug discovery

Background:

Monoclonal antibodies are crucial therapeutics across various medical areas.
Developability, assessing physicochemical properties, is key for successful drug progression.
Early evaluation of antibody developability is vital for efficient candidate selection.

Purpose of the Study:

To establish a high-throughput workflow for assessing monoclonal antibody developability.
To correlate biophysical properties with downstream process parameters.
To enable early elimination of suboptimal antibody candidates.

Main Methods:

Analysis of 152 monoclonal antibodies using biophysical property assays.
Implementation of a high-throughput workflow for early-stage screening.
Evaluation of binding affinity, biological properties, and physicochemical parameters.

Main Results:

Established correlations between different biophysical assays.
Demonstrated that physicochemical properties correlate with downstream process parameters in case studies.
Successfully eliminated antibodies with suboptimal properties through the workflow.

Conclusions:

The developed workflow efficiently ranks antibody candidates based on developability.
Early identification and engineering of problematic antibody attributes are facilitated.
Streamlined candidate selection accelerates the CMC phase and overall drug development timelines.