This talk explores the integration of data science and AI in biomedical research, focusing on four key types of data analysis: descriptive, exploratory, predictive, and prescriptive. We will discuss how these methods, combined with advanced technologies like knowledge graphs (using Neo4J) and large language models (LLMs) from HuggingFace, are transforming the way biomedical data is analyzed and interpreted, driving innovation in drug discovery and clinical research.

The Human Omics Hub focuses on integrating multi-omics data management, starting with the UK Biobank. However, fragmented pipelines hinder scalability. This study employs large language models (LLMs) to automate standardized Nextflow pipeline creation for multi-omics data processing. By merging LLMs with expert input, we optimized the development process, significantly reducing coding time and costs while accelerating real-world evidence generation from diverse omics data, including EHR and genomics.

This presentation will explore the transformative potential of supercomputer-driven in silico trials for assessing cardiac drug safety. By employing advanced electrophysiological models of the human heart, we will demonstrate how these virtual trials can accurately predict drug-induced arrhythmias and QT interval prolongation, reducing reliance on traditional testing methods. Attendees will gain insights into integrating multi-scale modeling and AI into precision medicine, offering a scalable solution to enhance drug safety while minimizing costs and improving outcomes.

As the world's largest publicly available repository of raw sequence data, the Sequence Read Archive (SRA) plays a pivotal role in advancing public health and life sciences research. This presentation highlights state-of-the-art tools and strategies for managing and analyzing the SRA’s massive datasets, showcasing its impact on infectious disease surveillance, genomic epidemiology, and precision medicine. Discover how innovative informatics solutions are transforming raw data into actionable insights for global health challenges.

With AI taking center stage in coding, research teams are leveraging AI-enabled IDEs to refactor legacy systems into modern, efficient languages. This talk presents a balanced view of generative AI-supported coding, cutting through the hype to focus on real-world applications. Discover practical strategies and examples of how AI is transforming outdated research systems into scalable, maintainable, and future-ready platforms for life sciences.

Since 2010, “Trends from the Trenches” has been a cornerstone of the Bio-IT program, delivering candid and occasionally blunt assessments of the most impactful and overhyped IT technologies in life sciences. This talk will provide a deep dive into computing, storage, cloud, data science, machine learning, and more, with a focus on supporting data-intensive science. Looking ahead, this talk will share forward-thinking predictions about emerging technologies and trends poised to shape the future of life sciences innovation, offering actionable insights for navigating the next wave of IT evolution.