As part of SciLifeLab, we support various academic projects through computational chemistry and machine learning (ML) calculations. Developing new drugs is both costly and time-intensive, but SciLifeLab’s Drug Discovery and Development (DDD) platform aims to transform this process. By advancing early-stage hit identification using DNA-encoded chemical libraries (DECLs) and leveraging ML to analyze 4.4 billion in-house DECL compounds, DDD seeks to optimize drug discovery pipelines using machine learning and deep-learning approaches. Many of the ML models produce vast amounts of data, and centralized storage would streamline calculations and facilitate efficient ML/DL workflows.