Experts in data sciences achieve new levels of operational insight through real world data.
Sponsors benefit from label expansion, analysis of data for marketed products, and reduction in duration and number of clinical trials.
The data science experts at MMS open new possibilities for sponsors searching for data-driven insights. The team employs flexible analytics tools that focus on the highest quality deliverables for projects using big data and real world evidence. Through a proven process, the data sciences team is able to utilize real world data to shed light on disease, compound, patient, and operational insights for a variety of pharmaceutical and healthcare applications.
This four-step approach includes:
1. Discovery: Identify where MMS can leverage data for making better business decisions, define goals and objectives of the analytic approach.
2. Data Engineering: Gather data requirements, collect and build understanding of the data, clean and prepare data for analysis.
3. Algorithms and Analytics: Analyze and refine the cleaned data to develop the model and analytics that pertain to the business problems.
4. Share and Decide: Share valuable results and develop actionable insights with stakeholders, garner feedback, and repeat methodology as necessary.
Health Analytics Collective
Along with MIT, the Center for Translational Medicine at the University of Maryland, and Julia Computing, MMS is a co-founding member of the Health Analytics Collective – a pioneering group that strategically uses real world evidence in drug development. The collective brings proven regulatory expertise, strong processes, and the latest technology to provide data-driven insights, with a goal to shorten drug development timelines of new treatments.
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RWE to Support an Orphan Drug Application
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