This course introduces you to how Real World Data/Evidence can be used for pharmaceutical research and development and how it complements the evidence package for healthcare decision-making. If you are interested in applying data science to pharmaceutical research using data collected as part of routine clinical practice, this course is for you.
Data Science with Real World Data in Pharma
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
9 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Explain how real world data/evidence fits into the drug development process
Describe the three major types of bias that can be encountered in observational studies
Apply basic survival analysis techniques such as Kaplan-Meier plots and Cox Models to synthetic data.
Details to know
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Recently updated!
February 2025
Assessments
5 assignments
Taught in English
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There are 5 modules in this course
In this module we briefly introduce the phases in drug development and the evidence generation process to bring treatments to patients. We then exemplify how real-world data/evidence fits into the drug development.
What's included
5 videos4 readings1 assignment1 discussion prompt
In this module, we explore the limitations of real-world data. We discuss several sources of real-world data and explain their strengths and weaknesses. We then create clearer definitions of the types of bias that can be encountered when exploring real-world data.
What's included
3 videos1 assignment2 discussion prompts
In this module we explore study designs for observational data and methods to control for bias (systematic errors). We also mention concrete examples used in pharmaceutical research.
What's included
3 videos4 readings1 assignment1 discussion prompt
In this module we will design and conduct our own study using synthetic data to explore the concepts learned in modules 1-3.
What's included
5 videos1 assignment1 discussion prompt3 ungraded labs
In this module we consider the point of view of two critical stakeholders: regulators and payers. We see their position about real world data/evidence and its acceptance. We also explore specific use cases of how real world evidence has been used in practice.
What's included
3 videos4 readings1 assignment2 discussion prompts
Offered by
Recommended if you're interested in Data Analysis
University of Colorado System
University of Colorado System
University of Colorado System
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