Bio-IT World Conference & Expo Europe

Track 1: R&D in Pharma
Drive Precision Medicine through the Digitalization of Pharma R&D

The R&D in Pharma track will explore key challenges and solutions around developing and scaling key workflow, processes, and infrastructure to manage data generated via new technologies and services, and support an effective informatics ecosystem while meeting scientific, business, and regulatory demands. We will explore tools and technologies being leveraged to elevate data to insights and impact, data and analytics strategies to optimize decision-making, and novel approaches to utilizing artificial intelligence, machine learning, and natural language process to drive innovation in R&D.

Track 2: AI for Pharma
Leverage AI to Accelerate Drug Discovery and Development Efforts

The AI for Pharma track will explore the application of artificial intelligence and machine learning technologies to maximize and accelerate drug discovery and development efforts from early-stage adoption to practical application. Presentations will explore the role of artificial intelligence and machine learning in transforming disease understanding and target ID, approaches using AI and human expertise to help identify and deliver validated targets, as well as enhancements to chemical drug design and precision medicine. We will also explore how AI/ML efforts compare to tried-and-true successful discovery (drugs-to-market) methods.

Track 3: Storage Infrastructure & Cloud Computing
Implement Technology Infrastructure and Storage Solutions to Support Innovation and Data Strategies

The unprecedented growth of data generation and research storage isn’t slowing down anytime soon. As such, storage is becoming a major cost element where organizations are spending millions on systems and platforms. Cloud computing has been a platform solution for years and while this is maturing, innovations and applications continue to evolve. The role of data engineering is critical in orchestrating, configuring, managing, and monitoring solutions to manage the data bloat problem. The Storage Infrastructure & Cloud Computing track assembles thought leaders and organizations who will share case studies on advances in large-scale data management, predictive analytics, workflow automation, governance, and cloud computing to advance research and facilitate collaboration.

Track 4: Data Management
Implement Data Management Solutions to Satisfy Increased Computing Power Demands

With the increased demand in computing power from life science researchers and scientists tackling big data issues, data storage infrastructure must be able to scale to handle billions of data points and files efficiently. The problem is administration of data to ensure information can be integrated, accessed, shared, linked, analyzed, and maintained to effect change across the organization. How do you make sense of data and its content to create value? The Data Management track will explore these questions and other themes related to FAIR data, data reuse/governance/literacy, data federation, and standards/data curation/harmonization.

Track 5: Bioinformatics
Utilize Computational Tools and Resources to Turn Data into Actionable Knowledge

The Bioinformatics track will assemble thought leaders who will present case studies using computational resources and tools that take data from multiple -omics sources and align them with clinical action. Generating real-world data for real-world evidence solutions can lead to real-time assistance in disease prevention, prognosis, diagnostics, and therapeutics. With the ever-increasing volume of information generated for curing or treating diseases and cancers, bioinformatics technologies, tools, and techniques play a critical role in turning data into actionable knowledge to meet unstated and unmet medical needs.