The Therapeutics Evidence Accelerator was comprised of two interactive workstreams: the Evidence Accelerator Collaborative and the Parallel Analysis Workgroup.

Therapeutics Evidence Accelerator Collaborative

Interested data partners shared findings on critical questions during Therapeutics Evidence Accelerator Lab Meetings. Results were generated and analyzed in many different ways and using different methods and data sources. The Lab Meetings provided a “safe collaborative space” for key players across the health data ecosystem: FDA, major health data/technology organizations, academia, professional societies, health systems, insurers, and drug and device industries, to assimilate and evaluate data generated from across the country. Past meetings explored topics such as the impact of COVID-19 on cancer patients, the potential role Artificial Intelligence can play in COVID-19 research, and a discussion advancing when, where, and how to make the best use of real-world evidence.  See Lab Meeting Summaries.

Nearly 120 organizations participated in the Therapeutics Evidence Accelerator Collaborative meetings, including the following:

  • Aetion
  • APANDEMIC.ORG
  • Center for Medicine in the Public Interest
  • Ciox Real World Data
  • COTA
  • Datavant
  • Duke-Margolis Center for Health Policy
  • Flatiron Health
  • Health Catalyst
  • Health Verity
  • HealthPals
  • IQVIA
  • Johnson & Johnson
  • Lilly
  • Mayo Clinic
  • OHDSI
  • Panalgo
  • Pfizer
  • Roche
  • Sanofi
  • Syapse
  • Syntegra.io
  • TriNetX
  • UnitedHealth Group

Therapeutics Evidence Accelerator Parallel Analysis Workgroup

We worked closely with FDA to develop key research questions that multiple organizations and teams can address simultaneously. Initial activities of this work stream include (1) rapidly revising a list of core data elements; (2) identifying those critical to answering the primary question; and (3) establishing uniform collection parameters. It was necessary to work collaboratively to determine how data elements are being extracted and how they were being defined in order to operationalize a platform that could not only answer questions, but also inform how research activities could be conducted in the future.

Repeating analyses in parallel by collaborators using different analytical techniques and data sources will help strengthen findings and learnings. Furthermore, this effort will help validate the role of real-world data as a tool for rapidly learning about patient characteristics, treatment patterns, and outcomes associated with management strategies for COVID-19.

Three initial research areas (the use of hydroxychloroquine and azithromycin in hospitalized patients; the use of remdesivir; and the natural history of coagulopathy in COVID-19 patients) enabled the Therapeutics Accelerators to establish methodologies and processes for creating common data elements and interoperability. A critical early result of the Evidence Accelerator has been the characterization of the natural clinical history of COVID-19—foundational to ensuring testing performance, identifying treatment, predicting immunity, detecting potential for future waves of infection, and tracking mutation. 

Nearly 60 organizations participated in the Therapeutic Evidence Accelerator Parallel Analysis Workgroup, including the following:

  • Aetion
  • Ciox Real World Data
  • COTA
  • Datavant
  • Duke-Margolis Center for Health Policy
  • Flatiron Health
  • Health Catalyst
  • Health Verity
  • HealthPals
  • IQVIA
  • Mayo Clinic
  • OHDSI
  • Roche
  • Syapse
  • TriNetX