Build your COVID-19 Research Program with Flywheel and Google Cloud
Apply for COVID-19 research offers and credits from Flywheel and Google
Flywheel has partnered with Google Cloud to provide special pricing and credits for qualified COVID-19 research projects.
Flywheel streamlines and accelerates your COVID-19 research program with a comprehensive research data management solution for medical imaging and related non-imaging data. Today, Flywheel works with leading global research institutions to manage their medical imaging data (MR, CT, PET, Ultrasound, and others), clinical data, and associated processing for large-scale academic and clinical research. Flywheel enables data collection and de-identification, secure multi-site collaboration, curation and annotation, preprocessing and pipelines, and analysis deployed Google Cloud Platform (GCP).
Flywheel is offering special pricing and credits for qualified projects, including use of Flywheel on Google Cloud at no cost while longer term funding is being established. Flywheel is also offering services to help speed deployment of your project.
Google is also offering credits for qualified COVID-19 researchers. Google Cloud research credits can be used for most computing services on GCP such as storage, compute, and data analysis, including those related to the deployment of Flywheel’s research data management platform.
To apply, interested researchers should describe their research problem, project timeline, and the GCP tools they intend to use. Applicants must be verified researchers from a commercial, nonprofit, government or academic research institution. Applications will be reviewed on a rolling basis during the COVID-19 pandemic.
Apply for the Flywheel and Google Cloud Platform offering in this interest form.
Flywheel Launches Enterprise-Scale Medical Imaging Solution for Life Sciences
A digital transformation is underway in the Life Sciences and organizations are motivated to reduce R&D costs, improve operational efficiencies and shorten drug development timelines. To be successful, these organizations need to cost-effectively leverage high-quality data for the exploration of new solutions and reuse data collaboratively within data science & research teams. However, traditional R&D infrastructures are insufficient for large-scale data collection, complex data validation, automated quality controls, and scaling processing (and AI) pipelines.
Next-Gen Imaging Research Platform to Drive R&D Efficiency and AI Initiatives
Flywheel offers a scalable research-first platform that can capture imaging and related data from multiple siloed sources, including CROs and historical clinical trials. Flywheel integrates with existing data pipelines and software tools to ingest multi-modal data, and then consolidate, curate, validate, and disseminate that data to analytics and machine learning platforms. With the provenance to support regulatory approvals and scientific reproducibility, Flywheel supports secure collaboration to solve problems with multi-disciplinary teams internal and external to organizations.
Now with Flywheel for Life Sciences, the solution incorporates new enterprise scaling features that help support the needs of large, global life sciences organizations and their massive volumes of data from diverse sources all over the world. These features include high speed bulk loading, horizontal and vertical scaling, version control deployments and the provenance to support audit readiness.
Cloud-Scale Solution Backed by Professional Services
Flywheel for Life Sciences leverages the full power of modern cloud computing to deliver a fully managed service allowing digital, operations, data, and clinical teams to focus on research and results rather than IT. The Flywheel team partners with life sciences organizations to tailor and deliver a system that meets enterprise requirements and critical schedules.
“We are excited to launch our Life Sciences solution to streamline and leverage imaging data assets and machine learning workflows, helping organizations increase R&D efficiency and accelerate drug discovery,” said Travis Richardson, Chief Product Officer of Flywheel.
To learn more, please reach out to info@flywheel.io.
Improved Collaborative Workflows with Custom Roles and Permissions
Flywheel is committed to provide customization tools for a secure, collaborative workflow. Previously, Flywheel offered fixed, predefined roles and permissions for administrators to match to site users and project collaborators. Now, administrators can have complete control over user permissions and defining roles for projects using a simple interface.
Tailor Your Workflows With Custom Roles and Permissions
The Custom Roles and Permissions interface enables you to:
Align the Flywheel system with specific responsibilities of the users. Select user capabilities for project management, access to files and metadata, and computational permissions.
Ensure your workflow is consistent with your organization’s policies. Define roles that ensure your research process follows organizational policies for viewing, modifying, and deleting data.
Implement fine-grained control to prevent unauthorized use and reduce risk. Ensure data integrity by entrusting only specific users with the ability to modify data.
Easily coordinate on responsibilities in multi-site collaboration. Reflect the permissions collaborators need to have while observing multiple institutional procedures.
Flexible Controls Enable a Variety of Applications
For example, here’s how you might use custom roles and permissions:
- Data Managers in clinical trials can be restricted from viewing or modifying analyses.
- A statistician role can be created with permissions to run gears, perform analyses but are restricted from deleting or modifying underlying data.
- A compliance coordinator role can be created with limited permissions to view metadata and data only to ensure project contents are valid and complete.
Powerful Controls and Easy-to-Use
Custom roles are defined at the site level, enabling consistency in permission sets across the site. Controls over Flywheel permissions include a user’s level of access with data, which data permissions apply to, and other key operations like running analysis or downloading data.
Creating an "Analyst” role with limited project permissions but has the ability to work with analyses
Research groups may then select from the site’s defined roles for the roles that fit their workflow. Users are assigned a specific role or multiple roles at the project level.
Setting roles at the project level - Note that users can be assigned multiple roles
You may find additional information about setting User Roles & Permissions in our documentation.
New Web DICOM Uploader with Configurable De-Identification
Flywheel has extended the functionality of the Web-based DICOM Uploader in version 11.2 to support configurable rules for de-identification at the project level. With the new Web Uploader, users have an easy to use, zero-footprint solution for remote data collection with the ability to de-identify data in the browser, before upload to the Flywheel system. De-identification rules may be specified to meet the specific needs of any project, ensuring that PHI protocols are adhered to from the point of data ingestion.
Simplify Data Collection for Multi-Center Studies
The Web Uploader provides an easy-to-use solution for collecting data for multi-center studies including:
- Uploading DICOM data without needing to install additional software
- Configurable de-identification to meet project-specific requirements
- Automatically enforcing institutional de-identification policies
Rich Functionality, No Installation Required
No installation is required to upload data to Flywheel, simplifying the process for researchers with administrative or technical constraints at their location. Users upload uncompressed DICOM data via their web browser by picking a target project via the Select Project dropdown and dragging and dropping standard DICOM files into the Drop Zone.
To access the Web Uploader, select “Upload DICOM” in the Left Navigation Panel in the “DATA” group. After you drag studies or series to the Drop Zone, Flywheel will automatically parse the DICOM headers and present the target subject, session and acquisition labels for editing as needed. You may upload multiple DICOM studies or series at once.
De-Identification Enforced Before Upload
After editing/confirming your subject, session, and acquisition labels, data is de-identified locally before being uploaded to the Flywheel system.
De-identification rules are attached to a project. Administrators can configure de-identification rules for a given project by attaching a file named deid_profile.yaml in the Project → Information → Attachments pane the project menu. In order to ensure clear requirements for de-identification, the web uploader will not be available for a project unless there is a de-identification profile installed. If no de-identification is required, simply provide a profile with no rules.
Powerful Tool for Configuring De-identification Rules
De-identification profiles are simple YAML files that specify a DICOM tag and the de-id action you’d like to take on that tag.
Examples of possible de-identification actions include:
- Removing DICOM tags such as PatientID or AccessionNumber
- Replacing tag values with a hash or other value
- Date offsets to obscure dates
- Convert dates to age in years
- And more
Example:
Once de-identification preferences are set, the de-identified profile can be validated by uploading a DICOM and then viewing the tags in the native DICOM viewer. Testing of de-identification rules can also be done locally using the Flywheel CLI.
Example:
You may find additional information about the Web Uploader or uploading Non-DICOM data in our documentation.
Flywheel Wins Minnesota High Tech Association 2019 Tekne Award for Cloud Computing
Minneapolis, November 25, 2019 — Flywheel, a cloud-based biomedical imaging research platform, was awarded the 2019 Tekne Award in the Cloud Computing category by the Minnesota High Tech Association. The Tekne Awards, announced on Wednesday, September 20th, recognize companies bringing innovation to Minnesota’s science and technology industry.
Flywheel is a comprehensive research data platform for medical imaging, machine learning, and clinical trials. The company offers a range of solutions for life sciences, clinical, and academic research applications. Flywheel streamlines the entire research workflow including data capture, curation, computation, and collaboration. Flywheel’s platform runs on all the leading cloud platforms including Google Cloud Platform, AWS, and Azure, as well as private cloud infrastructures. By leveraging cloud scalability and automating research workflows, Flywheel helps organizations scale research data and analysis, improve scientific collaboration and accelerate discoveries.
“We are excited to be named the winner of the Cloud Computing 2019 Tekne Award. It is an honor to be recognized among a group of innovative organizations driving forward incredible advancements in science and technology. Flywheel is privileged to help the world’s leading life sciences, clinical, and academic researchers collaborate to solve healthcare challenges that impact the lives of so many people. Flywheel’s cloud-based research platform helps researchers do more science and less IT in their pursuit of healthcare discoveries,” said Flywheel CEO, Travis Richardson.
High Performance Computing (HPC) with Flywheel
Flywheel now provides additional support for customers’ existing infrastructure and workflows with two significant advances.
HPC with Singularity and Slurm
Flywheel has introduced support for High Performance Computing environments running singularity and Slurm. This integration enables users to save on computing costs and allows them to take advantage of significant investments made in existing computing resources. Flywheel Gears may be run on HPC clusters regardless of whether the Flywheel system is deployed on premises or in the cloud.
Rsync-like Data Access
CLI Sync provides users with an efficient method of syncing their Flywheel data with local file systems. This improved data portability allows customers to leverage pipelines and hardware not yet integrated with Flywheel. The rsync-like functionality ensures that only changes to data are migrated to local systems, thus saving time and cost.
Flywheel Introduces New Advanced Search
Flywheel augments its fast, powerful search tool with the introduction of Advanced Search, providing users the ability to construct complex queries and quickly pinpoint the data they need. When this feature is introduced, find Advanced Search by hitting ‘Enter’ in the Search Bar and clicking ‘Advanced Search’.
Visual Query Builder
Advanced Search features a visual query builder, providing even the least technical users with the ability to quickly and easily construct highly specific queries. Search queries may be saved for sharing and reuse.
Powerful SQL-Like Query Language
Users that are more familiar with SQL can manually construct queries using Flywheel’s simplified query language: FlyQL. FlyQL enables access to all metadata, including DICOM tags and custom metadata.
Search Image Annotations and ROIs
With more and more customers looking to Flywheel to manage large, diverse data sets for Clinical Trials and Machine Learning projects, the need for improved data management tools has come to the forefront. With advanced search, users will have the ability to quickly and easily locate data across multiple projects matching any number of criteria. AI Developers can search for annotated images, including by regions of interest (ROIs), and create machine learning training sets with ease. Researchers can quickly locate subjects based on custom metadata to create collections or run batch analysis directly from search results.
Flywheel Delivers FAIR Principles
The FAIR acronym is a nice way to summarize four important aspirations of modern research practice: scholarly data should be Findable, Accessible, Interoperable, and Reusable. The article describing the FAIR aspirations is excellent, and we recommend reading it. Some limitations of current practice are described here. Our company was founded to advance research and we embrace these principles.
Flywheel, software used by thousands of researchers, embodies tools and technology that deliver on the FAIR principles.
About Flywheel
Flywheel is an integrated suite of software tools that (a) stores data and metadata in a searchable database, (b) includes computational tools to analyze the data, and (c) provides users with both browser-based and command line tools to manage data and perform analyses. Our customers use these tools on a range of hardware platforms: cloud systems, on-premise clusters and servers, and laptops.
Flywheel supports users throughout a project’s life cycle. The software can import data directly from the instrument (like an MR scanner) and extract metadata from the instrument files that is stored into the database. Auxiliary data from other sources can also be imported into the database. The user can view, annotate, and analyze the data, keeping track of all the scientific activities. Finally the data and analyses can be shared widely when it is time to publish the results.
FAIR Data Principals Implemented
Findable
Flywheel makes data ‘Findable’ by search and browsing. The Flywheel search tools address the entire site’s dataset, looking for data with particular features. It is straightforward, for example, to find the diffusion-weighted imaging data for female subjects between the ages of 30 and 45. The user can contact the owners of the data for access, and the data returned by a search can be placed in a virtual project (Collection) for reuse and further analysis.
Search is most effective when there are high quality metadata associated with the data and analyses. Flywheel creates a deep set of metadata by scanning the image data, classifying them. Users can attach specific searchable key words and add data-specific notes at many places - from the overall project level, the session level, the specific data file or the analyses. Users can find data by searching based on these descriptions.
Accessible
Our customers frequently observe that there is a conflict between making data accessible (sharing) while complying with health privacy rules. We live in a world with privacy officers on the one hand and open data advocates on the other.
Flywheel delivers an accessible solution that is respectful of both principles. We implemented a rigorous user-rights management system that is easy to use. Access to the data and analyses is controlled through a simple web-based interface. The system implements the different roles that are needed during a project’s life cycle. At first perhaps only the principal investigator and close collaborators have access; later, additional people (reviewers, other scientists) might be granted access to check the data and analyses. When ready, the anonymized data and full descriptions of the analyses can be made publicly viewable. An effective system that manages a project through these stages is complicated to write, but Flywheel makes the system easy-to-use through its browser interface.
Interoperable
Most scientists have felt the frustration of learning that a dataset is available, but the file format or organization of the data files requires substantial effort to decode and use. The medical imaging community has worked to reduce this burden by defining standardized file and directory organizations. Flywheel is committed to using and promoting these standards.
Our experience teaches us that well intentioned file formats and directory organizations are not enough. Flywheel stores far more information than what one finds in the header of a DICOM or NIfTI file or the BIDS directory structure. Our commitment to interoperability includes reading in files and directories in these standards and even writing Flywheel data into these formats. Beyond this, we are committed to tools that import and export data and metadata between Flywheel and other database systems.
Flywheel is further committed to supporting the interoperability of computational tools. We have opened our infrastructure so that users can analyze data using Flywheel-defined containerized algorithms, their own containers, or their own custom software. The Flywheel standards are clearly defined based on industry-standard formats (e.g., JSON, Docker, Singularity) so that other groups can use them and in this way support computational interoperability.
Reusable
From its inception, Flywheel was designed to make data reusable. Users at a center can share data within their group or across groups, they can reuse the data by combining from different groups, and create and share different computational tools. The user can select data from any project and merge it into a new project. Such reused data is called a Collection in Flywheel. The original data remain securely in place, and the user can analyze the collection as a new virtual project. All the analyses, notes, and metadata of the original data remain attached to the data as they are reused.
Equally important, the computational methods are carefully managed and reusable. Each container for algorithms is accompanied by a precise definition of its control parameters and how they were set at execution time. This combination of container and parameters is called a Flywheel Gear, and the specific Gear that was executed can be reused and shared.
More
The FAIR principles are an important part of the Flywheel system. We have also been able to design in additional functionality that supports these principles.
- Security and data backup are very important and fundamental. The ability to import older data into the modern technology has been valuable to many of our customers.
- The visualization tools built into Flywheel help our customers check for accuracy and data quality as soon as the data are part of the system.
- The programming interface, supported by endpoints accessible in three different scientific programming languages, permits users to test their ideas in a way that gracefully leads to shared data and code.
Tekne 2019 Award Cloud Computing Finalist — Flywheel's Biomedical Imaging Research Platform
MINNEAPOLIS, Sept. 24, 2019: Flywheel.io, a leading biomedical imaging research platform provider and an essential building block for imaging artificial intelligence (AI) has been acknowledged as a finalist for the Minnesota High Tech Association 2019 Tekne Awards in the Cloud Computing category. For the past two decades, the Tekne Awards have recognized organizations that are leading-edge innovators in science and technology in Minnesota.
Flywheel has been named a finalist in the Tekne 2019 Cloud Computing award category for its Biomedical Imaging Research Platform. The Flywheel platform is a comprehensive scientific workflow for imaging data management, including data capture, curation, computation, and collaboration, all integrated to accelerate imaging research within clinical processes, collaborative multi-site studies, and scalable imaging AI initiatives.
Flywheel is designed to speed and improve imaging research and scientific discovery; from standardizing and structuring massive volumes of historical imaging data in life sciences for AI and Machine Learning, to reducing time and costs for clinical imaging device scanning (magnetic resonance (MR), positron emission tomography (PET), etc...) and study processes, to testing the functionality of research design, all while ensuring research projects adhere to scientific reproducibility, regulatory compliance, security, and collaboration mandates needed for National Institute of Health (NIH) funding requirements.
Flywheel’s ease-of-use and scalability make Flywheel.io one of the bioinformatic industry's most respected imaging research workflow platforms with global customers including Fortune 500 life science organizations, AI specialists, and dozens of top-tier NIH-funded imaging research centers at universities like Stanford and Columbia.
"We are honored to be named as a finalist for the Cloud Computing Tekne 2019 Awards. Flywheel is privileged to help principal investigators, data scientists, and imaging center directors build imaging research processes for the future...so they can do more science and less IT in their pursuit of healthcare discoveries," said Flywheel CEO, Travis Richarson.
“This year’s Tekne Award finalists demonstrate thought leadership and are spearheading technology innovation in Minnesota and around the world,” said Jeff Tollefson, President and CEO of the Minnesota High Tech Association. “We look forward to further recognizing these organizations at the 2019 Tekne Awards as well as highlighting the impressive science and technology community here in Minnesota.”
A full list of Tekne finalists and November 20 gala details are available online at tekneawards.org. The event emcee is Paul Douglas.
To learn more about the Flywheel - Biomedical Imaging Research Platform, go to https://flywheel.io
@Flywheel_io is honored to be a finalist for the Minnesota High Tech Association @MHTA 2019 Tekne Awards in the Cloud Computing category for its biomedical imaging research platform. Go to https://ctt.ac/peqbs+ to learn more about Flywheel. @Flywheel_IO #MachineLearning #ImagingResearch #Bioinformatics
About Flywheel - Biomedical Imaging Research Platform
The Flywheel - Biomedical Imaging Research Platform is the leading provider of scalable and collaborative imaging research processes in an easy-to-use and scientifically sound platform. Flywheel users are creating the building blocks of AI and machine learning based Precision Medicine in a demanding scientific and regulatory environment with high security, privacy, compliance, reproducibility, scalability, and performance requirements. Founded in 2012, Flywheel customers are using millions of imaging research data in Flywheel platform to transform the future of healthcare and medicine.
About the Minnesota High Tech Association (MHTA)
The Minnesota High Tech Association is an innovation and technology association united in fueling Minnesota's prosperity. We bring together the people of Minnesota's science and technology ecosystem and lead the way in bringing science and technology issues to leaders at Minnesota's Capitol and Washington, D.C. MHTA is the only membership organization that represents Minnesota's entire technology-based economy. Our members include organizations of every size − involved in virtually every aspect of technology creation, production, application and education in Minnesota.
Flywheel.io: Brad Canham | 612-223-7359 | bradcanham@flywheel.io
Minnesota High Tech Association: Claire Ayling | 952-230-4553 | cayling@mhta.org
Flywheel Partners with Google Cloud to Provide Clinical Researchers with Advanced Cloud Technology and Machine Learning for Medical Imaging
View the press release on Global News Wire!
