Analytics in life sciences and healthcare today is extremely data-intensive. Most research projects require extensive collaboration and utilize data from many locations generated by a large number of researchers. As IT infrastructure becomes harder to manage, science organizations are trying to decide between going to the Cloud or investing in on-premises resources for scientific computing. Unfortunately, the decision isn't that straightforward. There are many important factors to consider when deciding where to invest your time and money for your science. During the pandemic, and with a significant and persistent supply chain problem for purchasing hardware, many organizations have decided to make more use of the Cloud. However, many have started to see rising costs and lower availability due to that decision. In this presentation, we'll review the use cases for scientific computing (types of analytics, data storage, hardware capabilities, collaboration), the primary personas in most organizations that use and manage the technology, and the consequences and outcomes of making either the choice of Cloud or on-premises architectures as a solution to the needs of your organization.

This talk will highlight the end-to-end research platform to support the significant increase of sequencing and other omics data types generated at the Sylvester Comprehensive Cancer Center. Using a state-of-the-art hybrid cloud architecture, the Sylvester Data Portal (SDP) provides researchers with secure data storage, FAIR data management, intuitive data access and reproducible data processing workflows. SDP has been built with a focus towards both experimental and computational researchers by using an intuitive user-interface and well-documented API’s.

Organizations are looking for competitive advantage through digitalization by 10x faster processing of 10x bigger datasets. Traditional storage cannot meet rapidly escalating requirements for performance AND scale across on-premises and multi-cloud data centers. Learn how the WEKA Data Platform accelerates next-generation sequencing, Cryo-EM microscopy, and bio-imaging data pipelines all while lowering the cost of research and keeping your data secure.

Complete laboratory orchestration is critical in moving organizations forward on their digital transformation journey.  Although the goal is the same, each organization has its own complex and tailored scientific ecosystems, as well as its own unique set of processes and challenges. Leveraging innovative digital tools, technology, and software solutions will create a seamlessly connected ecosystem that will ultimately eliminate those challenges, enhance operations and improve efficiency throughout.

Research enterprises are generating orders of magnitude more data in relatively short timeframes. As a result, describing data for downstream discovery and making the data accessible--with appropriate access controls--to partners and collaborators is increasingly challenging. Ad hoc methods cannot keep up and place undue burden on researchers and system administrators, but data portals combined with fast networks are becoming more prominent as a means of enabling access to large datasets. We will demonstrate how the widely used Django web framework, integrated with the Globus platform, can improve data discoverability and collaboration.

Seqster provides instant interoperability to retrieve and harmonize clinical, wearable, and genomic data from distinct sources. The SeqsterOS automates real-time Real World Data (RWD) collection while improving the participant journey. Life science enterprises benefit from improved study participant engagement and retention. Study participants and researchers benefit from longitudinal health information essential for long-term observational studies and effectively conducting health economics & outcomes research (HEOR). SeqsterOS is FDA 21 CFR Part 11 Compliance for drug submissions. The operating system includes de-identification and tokenization of data e-consent, eCOA and ePRO for any clinical trial or study. Learn more at seqster.com.

This talk will address the real-world impact of healthcare analytics in mental health care and the potential to provide more targeted and effective treatments. Dr. Gentile will share the work of ieso and how their use of big data has resulted in improvements in many aspects of mental health care including but not limited to precision healthcare, diagnosis, triage, risk identification, appropriate treatment plan, attrition, and recovery rates. As well, she will discuss how big data is helping ieso to develop the next generation of digital therapeutics. 

Despite advancements in ontologies and workflow tooling, data integration and metadata harmonization remain a significant challenge from the earliest stages of discovery all the way to production. We present the Active Discovery Engine (ADE), a Netrias platform that uses machine learning techniques to perform AI-assisted data curation and integration. We will showcase examples that highlight term alignment, automated data joining, and custom analytics integration.

Even the most secure systems can fall victim to attack or disaster, and when security fails, a complete recovery plan is essential to get your organization back on its feet. Join us to learn about building a robust disaster recovery plan for physical devices, servers, SaaS, and more.

Deploying compute intensive workloads on the cloud can be challenging, especially when trying to unify workflows for various cloud providers. Each platform has their own tools for compute, storage, and security which require specific knowledge and skills to build frameworks around. In this session learn how Rescale provides a unified platform for high performance computing built for a multi-cloud environment, as well as how to leverage these tools to accelerate your simulations.