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Using real-world evidence to advance COVID-19 medical countermeasures

Developing a system of studies for rapid assessment of COVID-19 inpatient treatment safety and efficacy

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Aetion Evidence Platform (AEP) is a software that analyzes real world data (RWD) to produce real world evidence (RWE). This project is intended to use AEP to develop a framework and system of studies for rapid assessment of COVID-19 inpatient medical countermeasures. (Photo: Aetion)
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Aetion Evidence Platform (AEP) is a software that analyzes real-world data to produce real-world evidence. This project is intended to use AEP to develop a framework & system of studies for rapid assessment of COVID-19 inpatient MCMs. (Photo: Aetion)

Background | Project description | Project outcomes | Additional reading | Related links

Performer: Aetion 
Project leaders: Jeremy Rassen, ScD, MS and Nicolle Gatto, PhD, MPH
Contract value: $2,696,737
Project dates: September 2021 - August 2022

Background

COVID-19 has created an unprecedented challenge to public health and security, resulting in an urgent need for the rapid development and application of innovative methods and tools to assess FDA-regulated products. This health crisis is yet more urgent given the limited available treatment options for this highly contagious disease. As a result, promising new products are entering the market before trial completion (e.g., with the use of planned, interim analyses) through Emergency Use Authorizations or through narrow-use approvals. Additionally, clinicians are repurposing products already on the market to treat COVID-19, without a complete understanding of these products’ safety or effectiveness in the context of COVID-19. Real-world data (RWD) and real-world evidence (RWE) offer the ability to better understand (and use) COVID-19 prophylactics, therapeutics, and diagnostics, and for medical countermeasures (MCMs) overall.

The rapid assessment of inpatient treatments has emerged as particularly critical for effective COVID-19 care, because the majority of life-threatening cases of COVID-19 are treated in inpatient settings. While inpatient COVID-19 mortality rates have declined, hospital capacity remains critically low and many patients experience declined physical and mental health post-discharge.

Project description

This project will develop a system of studies for the rapid assessment of the safety and effectiveness of COVID-19 inpatient MCMs, which entails the following steps:

  • Define and prioritize key research questions;
  • Identify fit-for-purpose data sources;
  • Develop appropriate, validated, and applicable measurement algorithms to capture key exposures, subgroups, confounding variables, and outcomes;
  • Design template epidemiological studies applicable to a range of treatments;
  • Implement studies and generate transparent reporting using Aetion Evidence Platform (AEP); and 
  • Build and disseminate knowledge via peer-reviewed publications and other avenues. By doing so, this project aims to further data familiarity and protocol standards to support RWD analyses among the broader research community. 

Additionally, this project is designed to demonstrate how using a platform-based analytical approach furthers regulatory learnings on the use of RWE to inform decision-making. The work will also provide a scalable infrastructure for the rapid development and evaluation of COVID-19 inpatient MCMs, which can be applied for future public health emergencies.

Project outcomes

Key goals and deliverables for this project include: 

  1. Developing and implementing a framework to identify and answer urgent COVID-19 inpatient questions of interest;
  2. Protecting public health by reliably answering research questions and speeding time to insight using platform analytics;
  3. Advancing regulatory science around when, where, and how to use RWD and scientifically valid RWE generation methods to inform decision-making; and
  4. Disseminating key learnings through manuscripts or conference participation.

This contract is managed by the Office of Data, Analytics and Research in the Office of Digital Transformation. For more information, contact Sachin Shah at [email protected].
 

Additional reading

Related links

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