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DDF Overview
What is the Digital Data Flow initiative?
The Digital Data Flow (DDF) initiative aims to modernize clinical trials by enabling a digital workflow that allows for automated creation of study content and configuration of study systems to support clinical trial execution. This initiative will establish a foundation for a future state of automated and dynamic readiness that can transform the drug development process. Click here for a video describing DDF.What is the objective of the DDF initiative?
The objective of DDF is to automate and expedite the Study Start-Up process by revolutionizing how data flows across clinical trial systems, beginning with upstream (e.g., study builder) and downstream (e.g., electronic data capturing/EDC, clinical trial management system/CTMS) clinical systems. TransCelerate has collaborated to develop an open-source, vendor agnostic, study definition repository (SDR) reference implementation. The SDR's basis is a Unified Study Definitions Model (USDM), developed by CDISC, that standardizes the data model for protocol study definitions. The SDR reference implementation enables the format of information from a digitized protocol and other sources to be standardized and stored centrally. This allows the information to be passed to systems through application programming interfaces (APIs) used for study execution and data collection and reused throughout the clinical development lifecycle. In summary, DDF will combine data standards and a novel technology to enable the flow of data across all systems involved in the design and execution of a clinical trial. Click here for a video describing DDF.Who does the DDF initiative help, and what are the benefits?
This initiative will assist many organizations, including pharmaceutical companies, CROs, standards organizations, upstream and downstream clinical vendors, sites, regulatory agencies, technology companies, and the open-source pharmaceutical and IT communities. With DDF, organizations across the R&D ecosystem will be able to leverage the open-source code of the SDR reference implementation and develop a framework to deploy their own SDR implementations. Digital Data Flow (DDF) benefits include: - Minimized process hand-offs, data re-entry, and data format inconsistencies across study start-Up and execution - A foundation for data exchange and interoperability between clinical technology systems, leading to greater compatibility among systems, flexibility to sponsors, and improved clinical trial efficiencies - A more seamless flow of data leading to accelerated study start-up, and further enabling trials automation for sponsors and research partners - Harmonization of the data format that can support greater interoperability and spark innovation within the R&D ecosystem and across the clinical trial solutions landscape. Click here for a video describing benefits of DDF.What is the data standards solution and technology that will enable DDF?
Today’s manual processes with multiple human and technical hand offs are not a sustainable, effective way to approach clinical development. DDF envisions the digitization and automation of the flow of information to keep up with increasing demands of clinical development. The DDF initiative involves a multi-faceted program that includes (a) collaborating with the Clinical Data Interchange Standards Consortium (CDISC) to develop a standardized data model and (b) working with lead collaborators and other stakeholders to develop the SDR reference implementation. The approach comprises the following: Standards Collaboration: CDISC has developed a new protocol study definition standard called the Unified Study Definition Model (USDM), alongside controlled terminology and specifications for APIs to develop the USDM, CDISC engaged key stakeholders, including technology companies and vendors Study Definitions Repository Reference Implementation: The study definitions repository (SDR) is a novel central component aimed at using technical and data standards to facilitate the exchange of structured study definitions across clinical systems. The SDR reference implementation is a working model of the SDR based on the USDM. It has been deployed as open-source and is meant to be vendor agnostic.CDISC Unified Study Definitions Model FAQ
What is the Unified Study Definition Model (USDM)?
The model is a unified, consistent, and comprehensive approach to structure and represent study definitions (i.e., protocol) data. Study definitions in the study definition repository (SDR) conform to the USDM data standard. USDM includes a class diagram describing the study design elements, their attributes, and relationships between them. The USDM defines all elements needed to construct a study definition, from high-level study design elements, such as study phase, indication, objectives and endpoints, and eligibility criteria, to detailed study design elements included in the schedule of activities and assessments. CDISC has developed the USDM. Click here for a video describing the USDM. Click here to access the latest version of the USDM posted on CDISC.Where can I access the USDM?
CDISC developed the Unified Study Definition Model (USDM). To access details of the USDM, go to https://www.cdisc.org/ddf.How do standards developed through DDF relate to other existing standards such as ICH M11 or Vulcan HLF FHIR?
CDISC’s Unified Study Definitions Model (USDM) is the foundational data model developed as part of the DDF initiative. It defines standardized and structured data content for clinical trial protocols and is designed to facilitate sharing and reuse of trial data across studies and organizations. The USDM is an abstract model independent of any particular rendering e.g. as a Word document, or PDF etc. The ICH M11 Clinical electronic Structured Harmonized Protocol (CeSHarP) initiative also defines the structure and content for a clinical protocol but does so more from a document perspective, with the two primary components being a human-readable document template and an associated technical specification (https://ich.org/page/multidisciplinary-guidelines). The USDM content is a “superset” of the M11 content, encapsulating all the data elements defined for M11, as well as covering many other aspects of a clinical protocol in much more depth (such as the Schedule of Activities (SoA)). As such, an M11 document can be generated from the data content encapsulated in the USDM. HL7 FHIR is an interoperability standard that contains an information model based on standard constructs that can be used to contain elements from CeSHarP and USDM but has a much wider scope. FHIR also provides an infrastructure of tooling, servers and vendors to facilitate assured data transport, transaction management and persistence.Study Definitions Repository (SDR) FAQ
What is the study definition repository (SDR)?
A study definition repository (SDR) is a novel central component aimed at facilitating the exchange of structured study definitions across upstream systems (e.g., study builder) and downstream clinical systems (e.g., electronic data capturing/EDC, clinical trial management system/CTMS) used to execute a clinical research study. It uses technical and data standards developed by CDISC. The SDR reference implementation demonstrates the implementation of data and technical standards defined by CDISC as the first step toward digital data flow and will catalyze the broader development of an ecosystem of connecting products. The SDR reference implementation will also demonstrate the ability to flow digital study definition information between systems through API connections to systems such as study builders, EDCs, and CTMS, with the opportunity for many additional use cases to follow., While these systems will not be part of the SDR reference implementation per se, they could demonstrate the ability to send (e.g., study builders) and receive (e.g., EDC and CTMS) study definitions data. Click here to access a video describing the SDR reference implementation.Is the SDR reference implementation intended to be a commercial product?
No, the SDR reference implementation will not be a fully functional product. Rather, it will be used to demonstrate and test ecosystem connectivity and interoperability. The SDR reference implementation may enable others to develop innovative commercial products. By creating a reference implementation of an SDR, we hope to motivate vendors to align their products with it and thus incorporate the new data standards. This will allow sponsors to more readily adopt an SDR. Click here to access a video describing the SDR reference implementation.How would vendors use the SDR reference implementation?
Vendors can connect to the SDR reference implementation to test compatibility and use the code through open-source licensing. Vendors can also take advantage of the interoperability functionality by deploying their own version in a cloud-based Software as a Service (SaaS) model or by building their own compliant SDR using a technology they choose. In addition, sponsors can create an SDR based on the SDR reference implementation for their own use, adding new functionality if desired, with the ability to contribute to further development of the SDR reference implementation. Click here to access a video describing the SDR reference implementation.How did DDF select an open-source license?
DDF will use a permissive license, specifically Apache 2.0, for DDF. A permissive license allows users to download, copy, use, transform, improve, and distribute the licensed code, and to incorporate that code in larger applications, including proprietary software. Permissive licenses do not require the modified code or applications with which it is used or linked or into which it is embedded to be made available under the same terms; commercial license terms are permitted. This approach encourages adoption of an open-source solution particularly by technology solution providers. When paired with strong standards and solution governance practices, along with continued awareness-building of DDF across the ecosystem, we believe this will maximize uptake of DDF.This is a highly regulated GXP environment. Are regulators ready for open-source solutions?
Health authority regulations generally do not differentiate between open source and commercial software. From a regulatory point of view, pharma sponsors are accountable for the quality of the submissions and the required validation of computerized systems used to run clinical studies, collect and analyze data. FDA has its own GitHub repository where they make open-source solutions available. FDA has also sponsored the development of a clinical data collection app released under an open-source license.How will the open source content be curated for quality and consistency over time? Will this be managed through CDISC ongoing?
We will be implementing a review process for all of the open-source contributions via Github. As the USDM data standard will be a key part of that, all contributions will need to be triaged for those that need to be routed via CDISC’s standards governance process, vs things like simple bug fixes, modifications to APIs, adaptors or extensions. Active discussions are ongoing with CDISC and leveraging their experience with their COSA initiative to align and learn more.Getting Help