We are a Artificial Intelligence (AI) Drug Design and Discovery Research and Development company, applying Deep Learning (DL) and Convolutional Graph Networks (CGNs) with , which utilize either supervised training procedures that is the foundation of its proprietary Computational Drug Design and Discovery Platforms, which in turn creates multiple AI-Enabled Biotech startups and collaborating with Academia and Contract Research Organizations (CRO) end-to-end integration that aims to improve the linking of data elements, to enhance the linkages among all stakeholders in drug research, development, commercialization, and delivery.
We have a multi-cultural, multi-discipline leadership team with expertise in Startup Incubation, AI Research, Drug Research and Development capable of leading AI Research, Wet Lab Research and Integrated Platform Technology.
AI (DL) Engine
Quantitative structure-activity relationship (QSAR)-based computational model can quickly predict large numbers of compounds or simple physicochemical parameters. Various parameters, such as predictive models, the similarity of molecules, the molecule generation process, and the application of in silico approaches can be used to predict the desired chemical structure of a compound…
Computational scientists in the AI Research Lab identify a handful of promising drugs from a database of millions of molecules. These selected molecules are then physically tested by the Wet-Lab Research Team and the computational results are confirmed or refuted. Molecules which are confirmed with a wet-lab experiment are used to refine further computational searches.
AI-Enabled drug design and discovery platforms that are used by Biotech startup and Contract Research Organizations (CRO) and University Research Labs focusing on protein-based therapeutic drug discovery by exploiting Orthosteric ,Allosteric, and Functional data.