Medical product safety is critical for patients’ health and the success of a drug launched after R&D and clinical trials worth billions of dollars. However, the performance of a drug in the post-market scenario is often unpredictable. To identify the unsuspected safety signals, it is now necessary to access and use information from all available real-world data sources such as Claims, EMR, and Genomic (future) data sets.
With a deep focus on safety surveillance, FDA launched the Sentinel Initiative for patient safety in May 2008. The government body, since then, recommends the use of an active post-market risk identification and analysis system or ARIA (Active Risk Identification and Analysis). As a part of the FDA’s Sentinel Initiative, data from public, private, and academic sources would need to be collated and validated to identify safety signals.
Let’s compare active and passive surveillance to understand why Saama’s Active Safety Analytics for Pharma (ASAP) has the potential to revolutionize patient safety.
Passive or spontaneous surveillance is the current industry norm, which often leads to under-reporting any new treatment issues to the market. There is no regulation that patients, physicians, or caregivers have to comply with when it comes to reported related adverse events.
Typically, after a drug is launched and is already getting prescribed, pharmaceutical companies set up a reporting channel for physicians and patients to directly report any product interactions that may have caused discomfort. The reporting is not dependent on the severity of the event, but instead a judgment call. Hence, many potential safety issues tend to go undetected or under-reported.
Even if an adverse event is reported, it becomes a single data point with no context and no way to understand the real reasons that led to the event. It is also not possible to follow up on the patient’s health status and map a recovery trajectory. All the data points that could have made the drug safer slip through the reporting structure.
With active surveillance, pharmaceutical companies need not wait for adverse events to be reported. Leveraging the Sentinel Common Data Model allows them to draw insights from a wide range of credible data sources public, private, and academic.
With data from medical institutes, it is possible to track the journey of an adverse event and even determine if the event was directly related to the treatment or not. The incident may not be related to the treatment compound. Instead, the dosage or the combination of the existing medicines may have led to the event. The recovery of the patient involved in the event and any potential side-effects can be tracked for an extended period as needed through regular data updates.
While active surveillance is mostly associated with risk monitoring and tracking pathogen outbreaks, it can play a critical role in identifying high-risk patients and ensuring patient safety. As per the FDA mandate, pharmaceutical and life sciences companies would soon be required to switch to the active system to comply with the Sentinel Initiative.
For an effective active safety surveillance strategy, it is necessary to use the most advanced technology for leveraging such a massive volume of data from so many disparate sources. An AI/ML-powered analytics platform would be able to harmonize the data and find patterns and insights that would otherwise be missed.
Saama has collaborated with one of the Top 10 US Pharma companies and Harvard-Pilgrim to develop a pioneering product, ASAP (Active Safety Analytics Platform), that leverages FDA-recommended sentinel data models and TreeScan technology to identify safety signals.
It is a first of its kind, active safety surveillance tool that leverages data from a wide range of real-world sources. It features robust and comprehensive visual graphics to show insights in the most accessible way. It has configurable dashboards for various users with trackable regulatory parameters.
Visit the Active Safety Analytics for Pharma page to know more about the features and benefits.
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