Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Hybridoma Technology

Hybridoma Technology

Hybridoma technology is used for the large-scale production of monoclonal antibodies. Monoclonal antibodies bind to only a single antigenic determinant or epitope. Such antibodies are used in research, diagnostics, and disease therapy. The hybridoma technology established in 1975 by Georges Köhler and Cesar Milstein was awarded the Nobel Prize in Medicine in 1984 for revolutionizing research and therapy.
Hybridoma Selection
Commonly used fusion techniques — electroporation,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same authorSame journal

Predicting antibody self-association with sequence-structure fusion models: the central role of CSI-BLI in early developability screening.

mAbs·2026

Same author

Accurate prediction of asparagine deamidation in biologics using advanced machine learning models.

Briefings in bioinformatics·2026

Same author

High-throughput small-angle X-ray scattering reveals effective structure factor transitions linked to high-concentration antibody viscosity.

mAbs·2026

Same author

Automation and digitalization in drug product process development.

Journal of pharmaceutical sciences·2026

Same author

Recent Advances in Rabbit Oncology: Diseases, Diagnosis.

The veterinary clinics of North America. Exotic animal practice·2026

Same author

Risk Factors Associated with Generic Escherichia coli Presence in Fresh Produce Grown in Manure-Amended Soil in Certified Organic Farms.

Journal of food protection·2025

Search research articles

Related Experiment Video

Updated: May 16, 2025

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System

Published on: May 1, 2019

Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep

Lateefat A Kalejaye¹, Jia-Min Chu¹, I-En Wu¹

¹Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, Hoboken, NJ, USA.

|April 1, 2025

Summary

Researchers developed DeepViscosity, an artificial intelligence model, to predict antibody viscosity. This tool aids in selecting low-viscosity monoclonal antibodies (mAbs) for subcutaneous injections, improving drug development and delivery.

Keywords:

Antibody viscosity ensemble deep learning high-concentration formulations monoclonal antibodies

More Related Videos

Scalable High Throughput Selection From Phage-displayed Synthetic Antibody Libraries

Scalable High Throughput Selection From Phage-displayed Synthetic Antibody Libraries

Published on: January 17, 2015

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application

Published on: June 16, 2023

Related Experiment Videos

Last Updated: May 16, 2025

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System

Published on: May 1, 2019

Scalable High Throughput Selection From Phage-displayed Synthetic Antibody Libraries

Scalable High Throughput Selection From Phage-displayed Synthetic Antibody Libraries

Published on: January 17, 2015

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application

Published on: June 16, 2023

Area of Science:

Biotechnology
Computational Biology
Pharmaceutical Sciences

Background:

High viscosity in concentrated antibody solutions hinders subcutaneous injection development.
Existing computational models lack generalizability due to limited training data.

Purpose of the Study:

To develop accurate predictive models for screening monoclonal antibody (mAb) viscosity at high concentrations.
To create a tool that facilitates the selection of low-viscosity mAbs for improved drug development and administration.

Main Methods:

Measured viscosity for 229 monoclonal antibodies (mAbs).
Developed DeepViscosity, an ensemble of 102 artificial neural network models.
Utilized 30 sequence-based features from a DeepSP model for prediction.
Classified mAbs as low-viscosity (≤20 cP) or high-viscosity (>20 cP) at 150 mg/mL.

Main Results:

DeepViscosity achieved 87.5% and 89.5% accuracy on two independent test sets.
The model demonstrated superior performance compared to other predictive methods.
Successfully predicted viscosity for a large panel of 229 mAbs.

Conclusions:

DeepViscosity enables early-stage selection of low-viscosity mAbs.
Facilitates improved manufacturability and formulation properties for subcutaneous drug delivery.
Provides a webserver application for accessible use in antibody development.