Target and Biomarker Exploration Portal for Drug Discovery

The discovery of novel drug targets and precision biomarkers remains a major challenge in drug development, with traditional differential expression analysis often overlooking key regulatory proteins. Here, we present a novel, web-based bioinformatics tool designed to accelerate the drug discovery process by integrating large-scale biomedical data with network analysis techniques. This tool harnesses machine-learning approaches to combine multi-modal datasets, including human genetics, functional genomics, and protein-protein interaction networks, to decode causal disease mechanisms and uncover novel therapeutic targets and precision biomarkers for specific phenotypes. A unique feature of the tool is its ability to process large-scale data in real-time, facilitated by efficient cloud-based architecture. Additionally, the tool incorporates an integrated large language model (LLM), which assists researchers in exploring and interpreting complex biological relationships within the generated networks and multi-omics data. By offering an intuitive, interactive interface, the LLM enhances the exploration of biological insights, making it easier for scientists to derive actionable conclusions. This powerful integration of AI-driven network analysis, multi-omics data, and advanced language models provides a robust framework for accelerating the identification of novel drug targets, ultimately advancing the field of precision medicine. The tool is publicly available at https://pdnet.missouri.edu/.