Comprised of experts in protein science, biochemistry, biophysics, medicinal and computational chemistry, and discovery scientists with expertise in pre-clinical development, our drug R&D team is applying the integrated technology platform-based approach and our practical expertise across a portfolio of internal and external drug discovery programs spanning across a wide range of disease targets and indications.
We continue to develop and expand our research capabilities in other drug modalities, including peptides, antibodies, and RNAs.
By applying our integrated technology platform and similar underlying methodologies for small-molecule drug discovery, we are exploring AI-powered solutions for active peptide generation and prediction. Coupled with theoretical computation, experimental data and our expert domain knowledge, our AI-powered peptide function prediction model enables us to screen and recommend candidate peptide sequences to satisfy the specific needs and criteria of the research projects. Beyond in silico tools, we are building wet lab capabilities for peptide R&D. With a goal to further advance our research capabilities in peptide drugs, we have formed a collaboration with Resolute Bio Inc., or Resolute. We expect this collaboration will grant us access to the unique peptide platform and database developed by Resolute, whereas we facilitate the peptide discovery and research efforts by Resolute with our expertise in computational simulation and computation-aided molecular design.
For antibody drugs research, we focus on tackling potential antibody developability issues, which are affected by a variety of characteristics, including aggregation, viscosity, solubility, immunogenicity, stability, expression yield and post-translational modification. The developability may greatly affect the subsequent CMC process and clinical trials. Based on the features extracted from protein sequence and structure, we have built AI models that are able to predict various properties associated with an antibody’s developability and guide the improvement of unsatisfactory properties to increase the overall likelihood of success.