Interactive Discussions

Interactive Discussions are informal, moderated discussions, allowing participants to exchange ideas and experiences and develop future collaborations around a focused topic. Each discussion will be led by a facilitator who keeps the discussion on track and the group engaged. For in-person events, the facilitator will lead from the front of the room while attendees remain seated. For virtual attendees, the format will be in an online networking platform. To get the most out of this format, please come prepared to share examples from your work, be a part of a collective, problem-solving session, and participate in active idea sharing.

TUESDAY, SEPTEMBER 21 ● 11:00 AM - 12:15 PM

Track 7: Data Science and Analytics Technologies

Speaker to be Announced, Domo


Track 10: Clinical Research and Translational Informatics

VIRTUAL INTERACTIVE DISCUSSION: AI and Intelligent Technologies for Drug Discovery and Development
Jeff Evernham, Vice President, Product Strategy, Sinequa

  • The opportunities and challenges of using AI in drug R&D
  • Real-world use cases: successes, failures, and lessons learned
  • How AI can unlock unstructured data for use alongside structured data
  • Best practices for adopting intelligent technologies for drug discovery and development
  • Looking ahead: using Insight Apps to accelerate the drug pipeline


WEDNESDAY, September 22 ● 8:00 AM - 9:00 AM

Track 1: Data Storage Infrastructure

IN-PERSON INTERACTIVE DISCUSSION: Genomics Research at the Speed of Memory
Charles Fan, PhD, Co-Founder and CEO, MemVerge 
  • Genomics research has experienced extra-exponential growth in data as more cells are studied across more modalities.
  • The growth of data is slowing down time-to-discovery with loading data from storage, executing code with IO to storage, and single-threaded apps the main bottlenecks.
  • Big Memory Computing consists of DRAM, persistent memory, and memory virtualization software working together to accelerate time-to-discovery
  • Analytic pipelines using Big Memory load terabytes of data in seconds, execute code with zero IO to storage, and use in-memory snapshots to transform single-threaded into multi-threaded pipelines.
  • Analytical Biosciences, Penn State University, and TGen are 3 case studies demonstrate extra-exponential growth in data, a reduction in time-to-discovery up to 60%, and power of in-memory data services.


Track 2: Data Management

IN-PERSON INTERACTIVE DISCUSSION: Automating Data Integration & Harmonization: Challenge & Opportunity

Emerson Huitt, Founder & CEO, Snthesis, Inc

  • Fueled by automation and high throughput methods, life science data is growing at an exponential rate, creating more data about more aspects of biological systems than ever before.
  • The explosion in research data creates significant opportunities, but also exposes challenges in managing, integrating and utilizing this data at machine scale.
  • Discuss the opportunities presented by automating harmonization and normalization across disparate data sets.

Track 6: Pharmaceutical R&D Informatics

IN-PERSON INTERACTIVE DISCUSSION: Data Harmonization in the Cloud: Enabling Frictionless Access to FAIR Data in Pharma R&D

Mike Tarselli, PhD, MBA, CSO, TetraScience

  • Challenges in Pharma R&D (functional/scientific data silos, legacy systems and lack of end-to-end automation, inefficient workflows) block access to actionable insights
  • How does replatforming to the cloud propel pharma R&D innovation with frictionless access to FAIR data and enable data science applications
  • What steps can organizations take to build a digital strategy that enables FAIR data and processes, improving data integrity and maintaining rigorous quality standards


Track 10: Clinical Research and Translational Informatics
VIRTUAL INTERACTIVE DISCUSSION: Best Practices in Cloud Content Management to Accelerate Clinical Operations

Manu Vohra, Managing Director, Life Sciences, Box, Inc.
Ganesh Visvanathan, Cloud Product Manager, USDM Life Sciences
David Blewit, Vice President, Cloud Compliance, USDM Life Sciences
This discussion will cover common challenges in content management and provide guidance to improve the efficiency of clinical trials and reduce costs while remaining compliant and reducing risk. 

  • The complexity of clinical trials is increasing faster than ever and collaboration must happen with many stakeholders globally. 
  • Clinical operations need strict security and regulatory controls that don’t impede processes,
  • Clinical teams demand intuitive and cloud-based tools

Submit Your Speaker Proposal

Data Platforms and Storage Infrastructure