GigaGen Publishes Research Demonstrating the Potential of its Machine Learning Platform to Improve Antibody Drug Discovery and Development

GigaGen Inc., a biotechnology company advancing transformative antibody drugs for immune deficiencies, infectious diseases and checkpoint resistant cancers, and a subsidiary of Grifols, announced today the publication of a research article titled, “Predicting antibody binders and generating synthetic antibodies using deep learning,” in the peer-reviewed journal mAbs.

The article demonstrates the potential of GigaGen’s machine learning platform to improve the discovery and development of therapeutic antibodies. GigaGen’s machine learning models predict and generate sequences of antibodies that best bind to specific targets and can be used to later generate novel recombinant antibodies against those targets for potential therapeutic application.

Carter Keller, chief executive officer at GigaGen, commented, “This research demonstrates how GigaGen’s machine learning methods can be leveraged to mine and learn patterns in antibody sequences, offering further insights into antibody engineering, optimization and discovery. While the article focuses on two main oncology targets, PD-1 and CTLA-4, the potential application of our technology is widespread to multiple disease targets, and we are excited to continue exploring its applicability in the future.”