Data Science with Real World Data in Pharma
Ends soon! Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.
Data Science with Real World Data in Pharma
Instructors: Adriana Reyes
3,539 already enrolled
Included with
Ask Coursera
14 reviews
Recommended experience
14 reviews
Recommended experience
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
See how employees at top companies are mastering in-demand skills
There are 5 modules in this course
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.
The course will help you describe what it means to be a Real World Data Scientist in the pharmaceutical industry. You will discover the particularities of the data sources and learn how to generate high quality evidence and how that evidence is used by the stakeholders for decision making purposes. To be successful in this course, you should have a background in data analytics, statistics, or other technical fields. No experience in the pharmaceutical industry is expected. We thank Hannah Furby and Matt Secrest for her inspirational material.
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
5 videos•Total 21 minutes
- Course introduction•2 minutes
- Evidence generation process for decision making in drug approval•6 minutes
- Phases of clinical development program and how real world evidence fits•6 minutes
- Comparative effectiveness•6 minutes
- Module review•2 minutes
4 readings•Total 63 minutes
- Syllabus•3 minutes
- An Introduction to the Fundamentals of Randomized Controlled Trials in Pharmacy Research•30 minutes
- Biopharma companies should consider a new, integrated approach to evidence-generation strategies to better demonstrate the value of therapies to all stakeholders.•15 minutes
- Explore the RWE Navigator•15 minutes
1 assignment•Total 5 minutes
- Test module 1•5 minutes
1 discussion prompt•Total 10 minutes
- Knowledge sharing•10 minutes
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
3 videos•Total 15 minutes
- More detail on specific real-world data sources•5 minutes
- Description of types of bias•7 minutes
- Module review•2 minutes
1 assignment•Total 30 minutes
- Test module 2•30 minutes
2 discussion prompts•Total 30 minutes
- Drawbacks of specific data sources for a prostate specific question•10 minutes
- Examples of different types of bias•20 minutes
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
3 videos•Total 14 minutes
- Study designs•7 minutes
- Methods to control for bias•5 minutes
- Module review•1 minute
4 readings•Total 100 minutes
- Observational and interventional study design types; an overview•30 minutes
- Control of confounding in the analysis phase•30 minutes
- Explore E-value calculator for unmeasured confounding•10 minutes
- Ask the right question(s)•30 minutes
1 assignment•Total 5 minutes
- Test module 3•5 minutes
1 discussion prompt•Total 10 minutes
- Knowledge sharing•10 minutes
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
5 videos•Total 21 minutes
- Survival Analysis basics•10 minutes
- Synthetic data introduction•5 minutes
- Labs introduction•2 minutes
- Analysis Results interpretation•4 minutes
- Module review•1 minute
1 assignment•Total 30 minutes
- Test Module 4 •30 minutes
1 discussion prompt•Total 10 minutes
- New treatments for Prostate Cancer•10 minutes
3 ungraded labs•Total 120 minutes
- Python Primer (Optional)•60 minutes
- Preparing data for analysis•30 minutes
- Analysing the data•30 minutes
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
3 videos•Total 12 minutes
- Stakeholders perspectives and use cases in pharma•4 minutes
- A glance to advanced topics•6 minutes
- Course review•2 minutes
4 readings•Total 55 minutes
- Real-World Evidence — Where Are We Now?•15 minutes
- Value of Real-World Evidence in health technology assessment: lost in translation?•15 minutes
- Comparative effectiveness research•15 minutes
- Further reading material•10 minutes
1 assignment•Total 5 minutes
- Test module 5•5 minutes
2 discussion prompts•Total 25 minutes
- What do you see in common about the RWE acepted by HTA bodies?•10 minutes
- Summarize a use case and say what was the value added by RWE•15 minutes
Instructors
Explore more from Data Analysis
- Status: Preview
Course
- Status: Free TrialU
University of California, Davis
Course
- Status: Free TrialU
University of Colorado System
Course
Why people choose Coursera for their career
Learner reviews
- 5 stars
78.57%
- 4 stars
21.42%
- 3 stars
0%
- 2 stars
0%
- 1 star
0%
Showing 3 of 14
Reviewed on Feb 15, 2025
Great starter course about real world evidence, design of experiments for data scientists aiming to design better clinical trials and save patient lives
Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
More questions
Financial aid available,