Exploration of Real-World Data for Drug Safety Monitoring

Safety surveillance is an objective in the pharmaceutical and devices industry that becomes a challenge once the drug/device is approved for commercialization.

The US Regulatory Agency, Food and Drug Administration (FDA) has suggested to explore the use of real-world data (RWD) for safety monitoring (reference Carol A. Palmer), FDA.

The drug/device post-approval surveillance includes collection of chronic use, and wider and more heterogenous patient populations. Within this process, rare adverse events (AEs) can be identified. Also, the process can also gather AE data related to drug-drug or drug-food interaction not previously evaluated, patient intolerance and even patients’ errors while taking their product/using their devices.

RWD is used to fill out platforms like FDA AE reporting system (FAERS) Medwatch and Sentinel System related to healthcare insurance claims and billing data.

FDA also reviews social media (SSMM) and collaborates in a platform called FDA-patientslikeme research. This initiative gathers information on health, treatment history, biometric data, symptoms, lifestyle choices and assesses risk management interventions, collected by patients with the same disease and treatments in mind. It also gives tips for cost savings and quality of life, care coordination and finally, patient safety.

The regulated party can also offer sound data to sustain its safety claims. Relevant parties have developed platforms to collect and analyze their drug/device safety data. In a recent Fierce reference, Fierce Pharma, a group called Truveta, is working to address this need. Truveta is a group of U.S. health system providers giving service to 20,000 clinics and 700 hospitals. They use RWD from scientific literature, patient records, claims data, physician reports, patient forums, and patient self-reporting channels.

Truveta’s advanced analytics, studies patient care and outcomes for drug/device and has been able to detect, monitor, and prioritize safety signals faster and more accurately. Truveta uses artificial intelligence (AI) to normalize, process and de-identify the data. Insurance claims can further enrich the data by capturing all clinical care a patient has received.

Truveta enables users to identify AEs and their related data elements. This toolset can be used to create safety dashboards in real time.

In summary, RWD is recognized as a well-established monitoring surveillance method. Diverse data from Regulatory Agencies, Patient-derived platforms and health care providers can offer credible information on the drug/devices safety that we use every day.