Session

DescriptionThe cloud is providing increasing value in the pharma and material science domains. It enables access to a broad range of HPC and AI services and eliminates the need to lock-in a particular hardware choice for a long period of time, especially when the physical location of the hardware resources becomes less important provided certain security, compliance and cost requirements are met. In order to take full advantage of the wide range of heterogeneous architectures available, it is critical to continuously optimize and adapt algorithms and approaches to the changing computational landscape. In our minisymposium we will showcase four examples of innovative approaches to HPC and AI from the fields of drug design and material science. We demonstrate a computing-as-a-service approach to the unattended, system-agnostic thermodynamic stability prediction of the amorphous drug system and a web-based platform that gives experimentalists access to computational workflows directly from their laboratory workstation. Finally, we will present an automated workflow for reaction network exploration with the hierarchical AI-driven approach using the example of a catalyst for the asymmetric reduction of ketones and a crystal structure prediction study performed entirely in the cloud.