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
Data Science with Real World Data in Pharma
位教师：Adriana Reyes
访问权限由 New York State Department of Labor 提供
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您将学到什么
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.
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作业
5 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
该课程共有5个模块
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.
涵盖的内容
5个视频4篇阅读材料1个作业1个讨论话题
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.
涵盖的内容
3个视频1个作业2个讨论话题
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.
涵盖的内容
3个视频4篇阅读材料1个作业1个讨论话题
In this module we will design and conduct our own study using synthetic data to explore the concepts learned in modules 1-3.
涵盖的内容
5个视频1个作业1个讨论话题3个非评分实验室
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.
涵盖的内容
3个视频4篇阅读材料1个作业2个讨论话题
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学生评论
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RM
已于 Feb 15, 2025审阅
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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University of California, Davis
University of Colorado System
