Image by Peachaya Tanomsup
Accelerating pharma innovation depends on maximizing the value of biomedical data assets, including imaging data. Within research organizations, however, data is often underleveraged, siloed, and disorganized. This adds to R&D timelines and costs, hinders AI development, and prevents collaboration that can lead to breakthroughs.
How can companies address these data challenges with maximum buy-in and minimal disruption?
Our panelists discuss:
- The barriers to breaking down data silos in pharma
- Cues life sciences organizations can take from the FAIR data principles
- Tools for standardizing how data is captured, curated and shared
- How standardizing curation can speed AI development
- Examples of pharma successes in breaking down data silos
Presenters
- Dan Marcus, PhD; Chief Scientific Officer, Flywheel
- Costas Tsougarakis;Â Vice President Life Sciences Solutions, Flywheel
- Oliver Keown, MD; Managing Director, Intuitive Ventures
Featured Webinar
Inside the Mind of a Data Scientist: Anisha Keshavan
If you’re curious about how Flywheel’s openness and extensibility can come to life in the hands of a power user, don’t miss this chat with Anisha Keshavan, Senior Data Scientist at Octave Bioscience. Anisha talks with Travis Richardson, Flywheel’s Chief Strategist, about how she has applied Flywheel to accelerate Octave’s work in care management for multiple sclerosis.
Past Webinar Recordings
Accelerating Clinical Research with Automated Workflows for Personalized Transcranial Magnetic Stimulation Treatment
Stanford Medicine’s Brain Stimulation Lab is managing large volumes of complex psychiatric data in its research and clinical trials on treatment-resistant depression. Typical processing workflows for managing this volume and complexity of data are manual and time-consuming. The lab’s work with vulnerable patient populations demands a faster and more reliable approach. In this webinar, Dr. Azeezat Azeez, a Postdoctoral Research Fellow at Stanford, outlines her approach to automating research workflows that help clinicians accelerate their research and treatment planning.
Powering Secure Data Discovery Across a Global Network of Innovators: What Will It Take
In this webinar, Francisco Gimenez, Partner at 8VC, and Flywheel discuss the data challenges faced by the biomedical research community and real-life examples from teams that are developing collaborative data networks. They cover the therapeutic areas experiencing accelerated innovation with enhanced data discovery and how commercial organizations are collaborating with research institutions to streamline discovery.
Unlocking AI on Medical Imaging Data: Flywheel, Clara, and Pure Storage
There’s been a large increase in organizations using AI to extract insights from medical data. As the volume and diversity of medical imaging data increases, however, deep learning pipelines can easily be throttled by slow data loading. Getting DICOM images from a PACS into federated training applications like Clara can be a major workflow limiter. We describe the major components that impact the performance of a medical imaging AI workflow using Flywheel as the data curation and management platform.
Unlocking Precision Medicine: Streamlining Data Management for Multi-Site Traumatic Brain Injury Research
Precision neuroscience has the potential to revolutionize diagnosis, treatment, and rehabilitation for traumatic brain injury (TBI). In this webinar, learn how Dr. Geoff Manley, Professor and Vice Chairman of Neurological Surgery at UCSF, and TRACK-TBI colleagues leverage Flywheel to collect and curate medical imaging from 18 major research institutions around the country to enable shared imaging repositories and foster public-private partnerships. Dr. Manley will explain how using Flywheel to streamline cloud-based data and compute management has helped researchers study deep learning segmentation, identify new blood-based biomarkers, and develop diagnosis for TBI using information on prognosis.
Cloud-Scale COVID-19 AI Research and Collaboration in Radiology
Data management is a key component to developing AI software. Organizations need adaptable, scalable infrastructure that can provide access to curated data while maintaining strict privacy and compliance standards and supporting secure sharing across multiple institutions. In this webinar, learn how a small, investigator-initiated project developed into a valuable COVID-19 chest CT dataset using Flywheel’s research data management platform. You will also hear how Imbio is exploring the correlation between lung injury severity and patient prognosis, as well as developing AI to diagnose COVID-19.
CMU-Pitt BRIDGE Center Standardizes on BIDS with Flywheel
In this conversation with Dr. Timothy Verstynen, Co-Director at the Carnegie Mellon University – University of Pittsburgh BRIDGE Center, hear how the Center addresses the problem of increasing data complexity by supporting research collaboration and enabling open science at the point of data access. Flywheel’s Michael Perry discusses how the centralized platform streamlines BIDS in an end-to-end solution for data management and collaboration.
Solving Large Scale Medical Imaging AI Problems
Dr. John Garrett, Director of Informatics at the University of Wisconsin Department of Radiology, discusses the state of machine learning in medical imaging and his development of AI to diagnose COVID-19 using thousands of chest X-rays collected and curated in Flywheel. Brad Genereaux explains how NVIDIA facilitates rapid AI training and Travis Richardson overviews Flywheel’s ecosystem for collaboration between academia, clinical organizations and life sciences.
SCOPE: Accelerating Enterprise-Scale Medical Imaging R&D for Innovation and Discovery
Can Akgun, SVP of Business Development at Flywheel, discusses streamlining the ingestion of diverse data from internal and external sources and Flywheel’s ability to scale processing and support machine learning workflows.
Aunt Minnie Fall Conference: Scaling Data Management for Machine Learning
Travis Richardson, President and Chief Product Officer of Flywheel, discusses how a research-first data platform is the solution to scale clinical research, fuel innovation, and empower your researchers.
ISMRM 2020 Webinar: Multi-Modality Research with Flywheel
Chief Product Officer Travis Richardson discusses how Flywheel manages imaging and related non-imaging data.
ISMRM 2020 Webinar: Multi-Site Collaboration with Flywheel
Chief Product Officer Travis Richardson discusses how Flywheel can be used to share data and algorithms for multi-site research.
ISMRM 2020 Webinar: Enabling AI and Machine Learning Discovery with Flywheel
Chief Product Officer Travis Richardson introduces data management and curation tools an support for training machine learning in Flywheel.
OHBM 2020: Open Science, Reuse, and Reproducibility with Flywheel Webinar
Travis Richardson, President and Chief Product Officer, presents an overview of Flywheel as an open and extensible platform that support data reuse and reproducibility.
OHBM 2020: Data Curation and Machine Learning Presentation
Gunnar Schaefer, Co-Founder and Chief Technology Officer, discusses the machine learning workflow in Flywheel, including labeling, search, training and testing.
OHBM 2020: Automating BIDS Workflow with Flywheel
Dr. Maggie Mahan talks about curating BIDS data sets in Flywheel, exporting BIDS data sets, and analyzing BIDS data sets with Flywheel Gears.
