AI Drug Discovery

AI Drug Discovery Overview

AI Drug Discovery

Therapeutic antibodies are currently the most successful class of biological therapeutics, but the traditional antibody development process is quite cumbersome and has obvious limitations. Current common antibody drug discovery methods include hybridoma technology, phage display technology, single B cell antibody screening technology, etc. All current methods are based on wet experiments in the laboratory, so they face problems such as long cycles, high costs, and high failure rates. At the same time, among the majority of candidate antibodies that have been painstakingly expressed and purified, only a relatively small proportion have the biophysical and other properties required to become therapeutics (such as high concentration solubility, large-scale manufacturability).

We have developed a set of AI algorithm systems for virtually generating antibody drugs, conducting structural analysis and summarization of all antibody structures in the Protein Data Bank, inputting all result information into the constructed neural network system, and letting the neural network system learn the relationship between antibody structure and sequence, and the relationship between antibody structure and antigen structure. At the same time, we use information from antibodies that have already been medicated or are in clinical stages to train the neural network system, ultimately achieving the goal of generating specific antibody sequence and structural information given specific antigen structure and epitope information. It can generate therapeutic antibody sequences with high affinity for any given antigen epitope.

AI Drug Discovery Services

AI Drug Discovery
Nanobodies, known for their small molecular weight, high affinity, stability, permeability, and cost-effectiveness, have demonstrated tremendous potential in disease …
In silico developability assessment, transforming biomedicine by providing groundbreaking approaches to predicting antibody developability. Leveraging advanced computational insights, streamline research processes, enhance therapeutic product robustness, and accelerate innovative drug discovery.
Methods for humanizing antibodies
With our profound expertise, we optimize antibodies for human compatibility, boosting therapeutic outcomes. Reducing adverse reactions, we lay the groundwork for innovative, patient-focused personalized medicine, customized for each individual.
With the advent of the era of precision medicine, monoclonal antibody drugs have become a hotspot in biological drug treatment due to their high specificity and effectiveness. As the types of monoclonal antibody drugs increase and their applications widen, related immunogenicity issues gradually emerge. For patients, immunogenicity affects the safety and effectiveness of drugs, and even brings fatal new diseases to patients due to ADA and endogenous protein cross-reactivity; for enterprises, the risk of research and development greatly increases, and if ADA problems are discovered in the late stage of clinical development, it will result in heavy losses; for drug regulatory departments, immunogenicity has also become a top priority, and all biological drugs must have an immunogenicity evaluation before they go on the market to ensure the safety and effectiveness of the drugs.
Our comprehensive assessment of drug potential and immune responses guarantees therapeutic safety and efficacy. This rigorous process is vital in bridging the transition from lab research to successful clinical stage implementation.