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Hands On Clinical Reporting Using R
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Hands On Clinical Reporting Using R

Master clinical data reporting with R using industry-standard packages for SDTM, ADaM, and regulatory submissions.

Course Cost

₹ 2,699

Intermediate

Skill Level

18 Hours

Self-paced lessons

This intermediate course teaches practical applications of R in clinical data reporting, focusing on data flow from raw data to SDTM to ADaM to final outputs. Learn to use open-source tools and pharmaverse packages for efficient clinical trial data analysis and reporting.

Adrian Chan

Adrian Chan

Joel Laxamana

Joel Laxamana

English

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English

Adrian Chan

Adrian Chan

Joel Laxamana

Joel Laxamana

What you'll learn

  • Master SDTM and ADaM data transformation in R

  • Implement pharmaverse packages for clinical reporting

  • Create regulatory-compliant documentation

  • Develop static and interactive visualizations

  • Handle clinical trial data efficiently

  • Apply industry standard practices

  • Generate submission-ready outputs

Skills you'll gain

Clinical Data Analysis
R Programming
CDISC Standards
Statistical Programming
Drug Development
Data Science
Clinical Reporting
Health Data Standards

This course includes:

4.5 Hours PreRecorded video

20 assignments

Access on Mobile, Desktop, Tablet

FullTime access

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Certificate
Certificate

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Share your certificate with prospective employers and your professional network on LinkedIn.

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Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

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There are 8 modules in this course

This comprehensive course covers the entire clinical data reporting workflow using R. Students learn to handle data transformation from raw formats to SDTM and ADaM standards, create regulatory-compliant outputs, and utilize modern R packages from the pharmaverse ecosystem. The curriculum emphasizes practical, hands-on experience with real-world scenarios.

Hands On Clinical Reporting Using R

Module 1 · 42 Minutes to complete

Fundamentals

Module 2 · 1 Hours to complete

SDTM : Study Data Tabulation Model

Module 3 · 49 Minutes to complete

ADaM Transformations (Introductory)

Module 4 · 4 Hours to complete

ADaM Transformations (Advanced)

Module 5 · 6 Hours to complete

Static TLGs (NEST)

Module 6 · 3 Hours to complete

Interactive Data Displays

Module 7 · 2 Hours to complete

Conclusion

Module 8 · 2 Minutes to complete

Fee Structure

Payment options

Financial Aid

Reviews

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Adrian Chan

740

Students

1

Course

Adrian Chan has established himself as a key contributor to Genentech's data science initiatives, particularly in clinical reporting and R programming. As an instructor for "Hands On Clinical Reporting Using R," he helps develop and deliver practical training in clinical data analysis and reporting methodologies. His work at Genentech, a pioneering biotechnology company with over 40 years of industry leadership, focuses on making complex clinical data analysis accessible and actionable. His expertise in R programming and clinical reporting contributes to Genentech's mission of advancing healthcare through data-driven insights. Through his teaching role, he helps bridge the gap between theoretical data science concepts and practical applications in clinical research and reporting.
Joel Laxamana

740

Students

1

Course

Joel Laxamana has established himself as a data science professional at Genentech, specializing in clinical reporting and R programming. As an instructor for the "Hands On Clinical Reporting Using R" course, he helps professionals develop practical skills in using open-source R packages for clinical data reporting tasks. His teaching focuses on the clinical data flow process, from raw data through SDTM and ADaM to final outputs. His expertise includes working with CDISC standards and implementing data science principles in clinical settings. At Genentech, he contributes to the industry's transition toward open-source tools in pharmaceutical research, helping bridge the gap between traditional clinical reporting methods and modern data science approaches.
Leena Khatri

740

Students

1

Course

Leena Khatri has established herself as a Data Scientist at Roche/Genentech and serves as Product Owner of NEST (Tables, Listings, TLG-Catalog). As an instructor for "Hands On Clinical Reporting Using R," she specializes in teaching professionals how to use open-source R packages for clinical data reporting tasks. Her expertise includes managing and developing tools for creating standardized clinical trial reports and analyses. As Product Owner of NEST, she leads initiatives to streamline the creation of tables, listings, and graphs for clinical reporting. Her work contributes to the industry's transition toward open-source tools in pharmaceutical research, helping bridge the gap between traditional clinical reporting methods and modern data science approaches.
Stefan Pascal Thoma

740

Students

1

Course

Stefan Thoma has established himself as an Analytical Data Scientist at Roche/Genentech in Basel since 2021. His academic background includes a Master of Science in Methods, Cognition, and Perception from the University of Bern and a Master of Science in Statistics from ETH Zurich. His work focuses on developing open-source tools for pharmaceutical research, particularly through his involvement in the admiral R package, which is a key component of the Pharmaverse initiative. As a member of the Pharmaverse blog management team, he contributes to knowledge sharing within the pharmaceutical data science community. His expertise combines statistical methodology with practical applications in pharmaceutical research and development, helping advance data-driven approaches in drug development and clinical research.
Tatiana Alonso Amor

740

Students

1

Course

Tatiana Alonso Amor has established herself as a data science professional at Genentech, specializing in clinical reporting and R programming. As an instructor for the "Hands On Clinical Reporting Using R" course, she helps professionals develop practical skills in using open-source R packages for clinical data reporting tasks. Her teaching focuses on helping learners understand the clinical data flow process, from raw data through SDTM and ADaM to final outputs. Her expertise includes working with CDISC standards and implementing data science principles in clinical settings. At Genentech, she contributes to the industry's transition toward open-source tools in pharmaceutical research, helping bridge the gap between traditional clinical reporting methods and modern data science approaches.
Hands On Clinical Reporting Using R

Intermediate

Skill Level

18 Hours

Self-paced lessons

Course Cost

₹ 2,699

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.