Predicting Therapeutic Antibody Properties with Machine Learning
Once trained, machine learning algorithms can predict the properties of new antibody candidates, greatly speeding up the drug discovery process.
Once trained, machine learning algorithms can predict the properties of new antibody candidates, greatly speeding up the drug discovery process.
Generative AI models are a type of artificial intelligence that generate new data that resemble training data by understanding the underlying...
Phage display is a powerful technique for the study of protein-protein interactions and the discovery of therapeutic antibodies.
The key to the production of monoclonal antibodies (mAbs) lies in a specialized cell type known as a hybridoma.
By enabling high-throughput sequencing of entire B cell repertoires, NGS offers unprecedented insights into the diversity and dynamics of antibody...
Brentuximab Vedotin works by targeting and binding to a protein known as CD30 on cancer cells.
Trastuzumab emtansine (T-DM1) is a combination of the chemotherapy drug called emtansine and the monoclonal antibody trastuzumab.
CD30 is expressed in some tumor cells, making it a potential target for cancer immunotherapy.
Antibody-drug conjugates (ADCs) are therapeutic agents that consist of monoclonal antibodies that are linked to a small-molecule drug or a cytotoxic...
TNF inhibitors work by blocking the action of tumor necrosis factor, thereby reducing inflammation and relieving symptoms.