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Project Scope 

Any question related to real-world data may be answered in a style similar to stack overflow.


Problem Statement

Every organisation has internal documents of learnings and best practices for conducting research with real-world data. This could take the form of database quirks, standard cohort definitions and preferred algorithms. There is currently no open-source alternative to the internal documents, which leads to duplicated errors, slower learning at the individual level and slower advancement of real-world evidence at the industry level.


Problem Impact

Having an open-source option for these learnings to be recorded and shared will lead to less duplication of effort, faster evolution of the real-world evidence space, and ultimately better insights for participants and patients. Stakeholders include data vendors, pharma and any other entity that uses real-world data.



Project LeadsEmail 
David Hood (Axtria)

David.Hood@axtria.com

Alex Pearce (PHUSE Project CoordinatorAssistant

Alexandra@phuse.global


Status
colourBlue
titleCurrent Status
Q2 2023

New project approved. Calling for volunteers.



Objectives & Deliverables

Timelines

Project kick offQ2 2023
Create 5 seed example Q&A postsQ2 2023
Abstract to be posted on PHUSE education website to raise awareness of this forumQ3 2023
Email/social media campaign to raise awarenessQ3 2023
Publish questions Ongoing 

Starting Q3 2023, deliverables will be ongoing. The team will be responding to questions which are posted and may begin as soon as the location (website) is confirmed, ideally by

Q2 2023.
Status
colourBlue
titleCurrent Status

Q2 2023

New project approved

.

Calling for volunteers.Project Members OrganisationAbhishek DhanukaNovartisAbhishek Mishra GSKAndy RichardsonPHUSEBerber SnoeijerClin LineBree NewtonEvideraDavid HoodAxtriaDevaki ThavarajahDishant ParikhDocs GlobalElizabeth MerrallJohnson & JohnsonHelen GuoBayerJeffrey AbolafiaPinnacle 21Johnathan AssayagPhizerKarnika DalaRegeneronLakshmi ManthaEphicacyLikhita KolliGSKMarion BonnetIpsenMarta TallonJohnson & JohnsonMary Anne RutkowskiMerckMatt BaldwinAmgenMaya ReimbaevaPhizerMichael MartiencRocheNaga DontamsettyTakedaNate FreimarkThe Griesser GroupNimita LimayeInternational Data CorporationNitesh BalakrishnannairGileadParag ShiralkarSumptuous Data SciencesRabia AhmadGSKRahaiah Muvvala Inductive QuotientRitesh DhimmarGSKSangeeta BhattacharyaJohnson & JohnsonShannon HunterData Science InstituteSreejaIconSreekanth Reddy YasaIqviaTadeusz LewandowkiJohnson & JohnsonYen PhanCodLad