When it comes to drug safety, waiting for reports from patients and their doctors just isn’t good enough.
For decades, the FDA relied exclusively on patients, their doctors, pharma companies, and medical device manufacturers to report possible adverse events (AE) related to previously approved products.
While AE reports generated from this type of passive, or spontaneous, surveillance remain a valuable safety research tool, the FDA has known for some time that a more active approach was needed.
Active Safety Surveillance Got Its Start 13 Years Ago
In fact, around the same time as Big Data was really coming into its own, Congress mandated that the FDA improve safety signal detection by passing the FDA Amendments Act of 2007. In response, the FDA launched the Sentinel Initiative to “[transform] the way researchers monitor the safety of FDA-regulated medical products, including drugs, vaccines, biologics, and medical devices.”
After several years of development and an extensive pilot using computer programs to analyze massive amounts of healthcare data, the FDA’s Sentinel System officially launched in February, 2016.
Using real-world data from healthcare claims and electronic medical records (EMR) to generate real-world evidence, Sentinel can actively identify new and unsuspected safety signals that may warrant further investigation. Within Sentinel, the Active Postmarket Risk Identification and Analysis (ARIA) System formats data into the Sentinel Common Data Model so numerous health outcomes that occur after exposure to a medical product can be detected, monitored, and analyzed.
We’re Empowering Pharma with the Same Safety Capabilities the FDA Has
Recognizing the value of this capability and how it could empower pharma companies if they had their own version of it, Saama—in collaboration with Gilead Sciences, the FDA’s Sentinel Operations Center, and the Reagan-Udall Foundation for the FDA—has developed a commercially viable solution that lets sponsors leverage the Sentinel Common Data Model internally.
With the power to actively analyze vast amounts of claims and EMR data from third-party providers like IQVIA and Optum, pharma companies will be able to:
- Help pharmacovigilance stakeholders detect signals more accurately and make more informed decisions.
- Explore potential causal relationships between drug/outcome pairs.
- Respond rapidly and comprehensively to regulatory requests or potential findings.
- Gain insights into competitive products.
- Provide foundational components for other data science initiatives.
Saama’s solution, Active Safety Analytics for Pharma (ASAP), is designed to help pharma companies become more active when it comes to safety. Insights generated from this powerful real-world evidence engine will not only help ensure the safety and effectiveness of postmarket products but will also inform and accelerate future drug development.