Real World Evidence – Project Volunteer Board

Interested in joining one of the Real World Evidence Working Group Projects? The projects below welcome new volunteers.

Project Scope:

The scope of the project includes developing collaterals for submission of real-world data through mutual discussion, knowledge and experience sharing by industry colleagues. The collaterals will be developed by undertaking research of existing draft guidance documents on real-world evidence by regulatory bodies, and by analysing members’ lessons learnt from completed case studies. The scope of this project will include submission of real-world data obtained from primary and widely used real-world data sources. These may include key electronic health record sources, patient reported outcomes, widely used and accepted claims data sources, and other commonly used observational data. This project will also touch upon the data curation and ingestion processes pertaining to clinical operational as well as submission data. Since real-world data can come from a wide variety of sources, the scope of this project will consider the widely and most commonly used real-world data sources by industry and member companies.

Current Status:

• Blog on initial impact assessment of FDA guidance on DRG templates.

Regular Project Meeting Day/Time:

• Bi-weekly: Fridays 16:00-17:00 GMT

Key Skills:

• Experience with regulatory submissions in general

• Data standards expertise > CDISC + other standards such as FHIR, OMOP, and PCORnet

• Acquiring RWD

• Worked in a health care settings and used EHRs/claims data

Project Scope:

Within this project we will make a list of available data sources and pros and cons. We will discuss what documents and requirements we need to show the FDA in the pre-alignment meeting and we will try to point to or create an outline and/or requirements for those documents. If possible, we will align with the FDA on this.

Current Status:

• No update.

Regular Project Meeting Day/Time:

• Bi-weekly: Fridays 13:00-13:30pm GMT

Key Skills: (currently being reviewed by WG Leads)

Project Scope:

We aim to publish a white paper which shall explore multiple models available for missing data imputation and share with the wider group the potential of each model and its efficiency in dealing with different kinds of missing data. The model efficiency is compared using a single open-source simulated dataset. 

Current Status:

• Target to decide the data source and request stats to share the techniques to explore according to data type. Split teams to work on project set-up (Apache Spark) and create a GitHub Repository.

Regular Project Meeting Day/Time:

• Bi-weekly: Thursdays 12:30-13:30 GMT

Key Skills:

• Programmers/Data scientists: Experience in anyone of the mentioned programming languages – R, Python, SAS.

• Experience with imputation techniques would be of advantage (proc MI, MICE model etc).

• Statisticians who would like to support AI/ML models for imputation (depending on the data points to impute).

Project Scope:

The scope of the project includes developing awareness of data standards specific to real-world data to support regulatory purposes. Common data models (CDMs) and taxonomies that are specific to the most commonly used real-world data sources by industry, member companies and regulatory bodies across the globe will be in scope, such as electronic health record sources, patient reported outcomes, widely accepted claims data sources, and other commonly used observational data. OMOP and the OHDSI community will be the focus, and will be evaluated against other CDMs and standards (such as PCORnet, Sentinel and CDISC).

Current Status:

• Project Approved

• Calling For Volunteers

Regular Project Meeting Day/Time:

• Kick-Off Meeting: 6 March 14:00-15:00 GMT

Key Skills: (currently being reviewed by WG Leads)