Our Projects

This project introduces the "Chemical Space Navigator," a novel AI-based process developed by DeepLS for optimizing pharmaceutical drug candidates. By digitizing significant portions of the traditionally iterative and lab-intensive process, it aims to save costs, time, and reduce chemical waste. This project will enhance the existing GeneSys platform, targeting the optimization phase of drug development. This project is financially supported by the State of Hesse under the Distr@l program.

PlantGraph represents a cutting-edge approach to plant research, combining advanced GNNs and LLMs to build an integrated, multiomics knowledge graph. This innovative system offers unprecedented capabilities in predicting plant phenotypes and understanding the impacts of pesticides and herbicides effects in our crops, positioning it as a vital tool for advancing agricultural science.

Our two-part system addresses the critical need for specificity in RNA-targeted drug development. By leveraging cutting-edge AI and deep learning models, we create a robust solution that identifies binding sites and generates small molecule ligands with desired ADMET properties. This innovative approach promises to significantly advance RNA-targeted therapeutics, offering a compelling opportunity for investment and collaboration.

Our project aims to build an AI system capable of adapting to its environment, modeling biological development from the cellular level to complex organisms. This innovative approach combines advanced AI techniques with principles from artificial life, pushing the boundaries of current AI capabilities and offering transformative potential across multiple scientific fields.