(740a) Digital Threads for Data and Process Traceability and Reproducibility in Drug Discovery

This presentation demonstrates the impact of workflow automation in chemical engineering, highlighting how life sciences companies automate molecular and quantum dynamics analysis in pharmaceutical development. Using Rescale and Nextflow, a Fortune 500 life sciences customer saved time by automating manual data management, reduced duplication and re-work, and ultimately sped up the drug development timeline. By making complex workflows easier and more efficient, the customer reduces R&D costs and delivers new medicines to market faster, with greater confidence in their efficacy for patients.

Rescale works with leading life sciences companies to build digital threads that transform pharmaceutical development by connecting teams and automating complex scientific workflows. Digital threads play a central role in life sciences R&D, linking each step of the drug discovery process, from modeling simulation to data analysis, making it faster and easier for global teams from different disciplines to collaborate seamlessly from anywhere. Digital threads also provide a trace of the specific steps involved in producing consistent results, with modularity for teams to use their best-fit software and hardware technologies.

Using Rescale and Nextflow to build computational workflows for multi-step analyses, the example life sciences company provides their scientists and researchers with a digital thread of processes, data, and tools so they focus on answering key research questions. This approach improves accessibility and reproducibility of complex workflows critical for faster turnarounds in collaborative research, while enabling them to swap in any preferred commercial, open-source, and custom technologies. With Rescale and Nextflow, any collaborator can quickly automate chains of analysis from a variety of applications and teams involved have visibility of their process and data for greater speed and confidence in decision-making.