Data Science with Real World Data in Pharma

Data Science with Real World Data in Pharma

Instructors: Adriana Reyes

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3,061 already enrolled

5 modules

Gain insight into a topic and learn the fundamentals.

13 reviews

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

13 reviews

Intermediate level

Recommended experience

1 week to complete

at 10 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.

Skills you'll gain

Tools you'll learn

R Programming

Details to know

Shareable certificate

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Assessments

5 assignments

Taught in English

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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

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

Adriana Reyes

Genentech

1 Course 3,061 learners

Otto Fajardo

Genentech

1 Course 3,061 learners

Offered by

Genentech

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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

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