Empowering PVE through advanced data analytical for identification and monitoring of safety signals for drugs and medical devices
Identifying drug safety signals and monitoring drugs can be challenging due to the sheer complexity of the problem. Spotline SIMS (Signal Identification and Monitoring System) can transform your PVE drug safety and associated risk management strategy. SIMS allows organizations to proactively identify and monitor the safety of their products.
- Rudimentary tools to identify and study safety signals
- Older/slower analytical technology that gives limited information
- Passive surveillance associated with enhanced risks due to missed or delayed signal identification
- Reactive vs proactive monitoring of the safety signals
- Lack of continuous monitoring resulting in delays in reporting of adverse events to Health Authorities and potentially missed opportunities to warn patients and providers
Spotline SIMS (Signal Identification and Monitoring Platform)
- Continuous monitoring of large datasets for safety signals using Advanced Analytics technology
- Transforming raw EMR/Claim information to Common Data Model (CDM) to enable statistical analyses for ongoing drug safety monitoring and risk identification
- Intuitive User Interface (UI) assists and amplifies PVE users’ abilities to define queries and scan parameters
- Statistical modeling using TreeScan, Temporal Pattern, Bayesian Shrinkage and Meta-Analysis for signal identification and monitoring
SIMS solution is based on the latest analytics tools that are designed for processing and reporting on large datasets. Following are the components that comprise this solution:
SIMS is designed to handle large datasets using Hadoop and SPARK infrastructure for managing millions of rows of raw data from EMR and Claims data. System can run on Azure cloud with HDInsight, in AWS with EMR, or in provide cloud.
Common Data Model
One of the key building blocks in signal identification and monitoring systems is to transform raw data into a Common Data Model (CDM) per FDA recommended guidelines. SIMS leverages SPARK in memory processing to apply hundreds of data rules in order to transform the data into CDM such that statistical modeling can be applied for analysis.
SIMS has a built in dashboard for monitoring in-process queries, monthly/weekly queries submitted by the users. Users can access previous queries that were submitted and analyze the results.
In addition to the dashboard, users have the ability to define a new analytical query to run the scan.
SIMS has a built-in analytical engine that takes user queries and performs statistical modeling. The output report can graphically interface to allow for visual analyses of the results by risk management teams.