Real World Evidence
Discover opportunities to improve your patient’s lives leveraging your investments in Real World Data.
Saama’s Real World Evidence is a custom development service that is designed to meet your specific needs of data harmonization from multiple Real World Data (RWD) sources into a common structure such as Observational Medical Outcomes Partnership (OMOP) or Sentinel common data model. Our RWE specialist team enables you to gain greater insights on Comparative Safety & Efficacy Analysis and Clinical Study Planning leveraging RWE.
Harmonized RWD
The Challenge
Typically, life sciences companies subscribe to multiple RWD data sources by different business groups. The siloed data brings challenges in data processing and utilization of the data to support regulatory submissions.
How Saama Can Help
Saama’s Real World Evidence accelerator has standard routines for claims and Electronic Medical Records (EMR) data from various vendors and the library continues to grow based on client subscriptions to new data sources. Besides making the granular data available for analysis, Saama’s Real World Evidence service has built-in data to speed up common analysis. Pre-built and customizable data quality reports help assess the quality of data over time and identify the reasons for data issues.
The harmonized data can be directly accessed for analysis. Saama builds analytics capabilities on the harmonized model to enable non-technical users to derive insights such as:
- Cohort Identification
- Clinical Development Feasibility
- Natural History of Disease
- Population Characteristics
- Payer Market Focus
Active Safety Analytics
The Challenge
The Pharmaceutical industry currently monitors the safety profile of the marketed products through a review of spontaneous reports and literature. Though this approach has proved successful in identifying many new adverse events in marketed products, this process has some limitations that impose severe constraints on a comprehensive safety assessment.
How Saama Can Help
Saama’s Active Safety Analytics for Pharma (ASAP) leverages the FDA’s Sentinel Common Data Model and the Tree-Scan methodology for detecting safety signals. ASAP is the first validated active safety analytics custom built solution for the Life Sciences industry. ASAP mirrors the capabilities developed by the FDA through the Sentinel Initiative and empowers drug developers to:
- Identify potential new safety concerns during routine safety surveillance
- Understand the safety profile of the competitive products and see how they compare in terms of safety
- Identify all the drugs that are associated with a specific outcome
- Explore potential causal relationships between Drug-Outcome pairs
- Respond rapidly and comprehensively to regulatory requests or potential findings
