This hands-on workshop on offers a technical deep dive into the "Gene to Drug" pipeline, from analyzing multi-omics NGS data to designing therapeutic molecules. Participants will learn how to identify disease-relevant targets through multi-omics gene expression analysis, leveraging cutting-edge tools such as Seurat for single-cell data integration and Multi-Omics Next generation sequencing (NGS) analysis for a holistic view of multi-layered disease and patient datasets. The second part of the workshop will focus on computer-aided drug design, where attendees will gain practical experience virtual drug screening and protein design. We will cover molecular docking and perform molecular dynamics (MD) simulations with programs like GROMACS to study protein-ligand stability. Attendees will also be introduced to current methods for protein structure prediction using AI-based algorithms such as AlphaFold and RoseTTAFold and learn how to use these models for the rational design of novel protein binders and miniproteins using RFdiffusion. A dedicated session will cover the application of fundamental biostatistics principles and Python using libraries like Biopython and pandas for building robust and reproducible analysis workflows.