Computational approaches to small-molecule drug design, are routinely used to screen virtual libraries of large numbers of existing compounds looking for those that might match a newly discovered target to test in experimental assays. Small molecules are attractive for AI approaches in part owing to the availability of appropriate data to learn from, thereby enabling good predictions about new molecules to be made. Small molecules are well described by their chemical structure, which can be rendered easily in a format that can be used by computers. Based on huge amounts of high-quality data that have been amassed in public and industry databases in the past few decades, scientists have a good understanding of the physicochemical principles that underlie the behavior of small molecules. AI, with its ability to look at vast quantities of existing data and learn patterns, can then predict new small molecules with desirable properties, taking the computational screening process to a new level. Our AI-based software is also a key advantage to accelerate antibody-drug discovery programs.
With years of experience, CD ComputaBio can provide customers with professional services applying artificial intelligence for pharmaceutical projects. We are an international team of highly skilled structural biologists, medical chemists, and machine learning experts. Using our experience in computational science and advanced AI technologies, we can help to accelerate drug R&D processes. We have successfully accomplished many projects. We guarantee the finest results for our customers all over the world.
CD ComputaBio's scientists are dedicated to seeking innovative solutions for drug discovery and life science research. We integrate AI technologies in every step of the drug discovery process: from early discovery to late stage clinical development. Our platform has been applied successfully in the context of collaboration with multiple pharma, biotech, and academia. CD ComputaBio aspires to be a leader in the field of deep learning for drug discovery and personalized healthcare.