Clinical SAS: Data Management, Statistical Analysis, and Interpretation

Uplatz provides this in-depth course on Clinical SAS: Data Management, Statistical Analysis, and Interpretation. It is a self-paced course consisting of video tutorials. You will be awarded Course Completion Certificate at the end of the course.

Clinical SAS refers to the use of SAS (Statistical Analysis System) software in the clinical research and pharmaceutical industry, particularly for the analysis and reporting of clinical trial data submitted to regulatory authorities like the FDA (Food and Drug Administration) or EMA (European Medicines Agency).

In summary, Clinical SAS is a specialized area of SAS programming focused on the unique data management, statistical analysis, and regulatory demands of the clinical research field. Professionals in this area are vital for ensuring the accuracy and integrity of clinical trial data, which is essential for the development of new medicines and therapies.

What is Clinical SAS?

Clinical SAS is the application of SAS programming in clinical trials to:

• Clean, manage, analyze, and report clinical data

• Ensure compliance with GCP (Good Clinical Practice) and regulatory guidelines

• Generate outputs like tables, listings, and figures (TLFs) for Clinical Study Reports (CSRs)

How Does Clinical SAS Work?

1. Data Collection

   • Data is collected from trial sites and stored in databases (like Oracle Clinical or Medidata Rave).

2. Data Transfer

   • Data is transferred into SAS datasets, often in CDISC formats like SDTM (Study Data Tabulation Model).

3. Data Cleaning

   • SAS is used to perform checks: missing values, outliers, protocol deviations, etc.

4. Data Analysis

   • Statistical procedures and custom code analyze efficacy and safety endpoints.

   • Results are based on predefined Statistical Analysis Plans (SAPs).

5. Reporting

   • SAS generates TLFs which are included in regulatory submissions.

6. Regulatory Submission

   • Datasets and programs are often submitted in CDISC-compliant formats, including ADaM (Analysis Data Model).

Core Features of Clinical SAS

• Data Integration: Imports and processes data from various sources (EDC systems, clinical databases).

• Data Cleaning & Validation: Identifies and resolves data inconsistencies, missing values, and protocol deviations.

• Support for CDISC Standards: Built-in tools for SDTM (Study Data Tabulation Model) and ADaM (Analysis Data Model).

• TLF Generation: Creates Tables, Listings, and Figures for clinical study reports (CSRs).

• Automation with Macros: Uses SAS Macros to automate repetitive programming tasks.

• Advanced Statistical Analysis: Offers procedures for efficacy, safety, and survival analysis.

• Graphical Representation: Generates high-quality charts and plots for visual reporting.

• Regulatory Compliance: Supports FDA and EMA requirements, including 21 CFR Part 11.

• Audit Trail: Maintains logs of data manipulations for transparency and traceability.

• Double Programming Support: Facilitates validation through independent program replication.

• Custom Reporting: Flexible reporting options for different stakeholders (e.g., clinicians, regulators).

• Security & Access Control: Ensures data confidentiality and user-level access control.

• Integration with Clinical Tools: Works seamlessly with systems like Oracle Clinical, Medidata Rave, etc.

Reed Courses Certificate of Completion

Digital certificate - Included

Uplatz Certificate of Completion

Digital certificate - Included

• Clinical SAS - all lectures 45:03:47

  • 1: 1. Clinical Research Overview 41:49
  • 2: 2. Historical and Ethical background of Clinical Research and ICH-GCP Guidelines 55:13
  • 3: 3. Essential Documents in Clinical Research 48:20
  • 4: 4. Drug Development 59:27
  • 5: 5. Clinical Trial Process and Roles 59:27
  • 6: 6. Clinical Trial Design 1:04:21
  • 7: 7. Clinical Trial Monitoring 1:08:02
  • 8: 8. Glossary of Clinical Research Terms 57:41
  • 9: 9. Responsibilities of Sponsor 40:09
  • 10: 10. Site Selection and Responsibilities of Investigator and CRC 38:17
  • 11: 11. QA and QC Audit and Inspection 57:38
  • 12: 12. Non-Compliance, Fraud and Misconduct 36:25
  • 13: 13. 21 CFR part 11 58:02
  • 14: 14. Protocol Understanding 59:39
  • 15: 15. Clinical Data Management 49:31
  • 16: 16. Protocol Assignment 46:30
  • 17: 17. CRF Design and Format 49:40
  • 18: 18. CRF Design and Format demo 57:57
  • 19: 19. Clinical Data Standards 52:02
  • 20: 20. CDM Study Start Up 1:22:15
  • 21: 21. CDM - EDC Setup Concept 1:04:43
  • 22: 22. CDM - EDC Study Conduct Concept 56:51
  • 23: 23. CDM - EDC Study Conduct Discrepancy Management 48:41
  • 24: 24. CDM - Discrepancy Management 50:32
  • 25: 25. Data Management plan 1:04:01
  • 26: 26. Project Management for Data Manager 1:02:31
  • 27: 27. Vendor Selection and Management 50:35
  • 28: 28. Edit Check Design Principles 53:49
  • 29: 29. EDC Study Closeout 49:02
  • 30: 30. CDM Study Closeout 34:32
  • 31: 31. CRF Completion Guidelines 50:29
  • 32: 32. Database Validation and Programming 42:42
  • 33: 33. Laboratory Data Handling 50:20
  • 34: 34. External Data Transfer 34:06
  • 35: 35. Patient Reported Outcome 51:45
  • 36: 36. Investigator Meeting 48:55
  • 37: 37. Metrics in CDM 1:03:36
  • 38: 38. Assuring Data Quality 44:27
  • 39: 39. Measuring Data Quality 1:00:26
  • 40: 40. Safety Data Management 48:00
  • 41: 41. Safety Data Reconciliation 51:50
  • 42: 42. Medical Coding 1:01:17
  • 43: 43. Clinical Data Archiving 46:52
  • 44: 44. Data Entry and Processing 49:59
  • 45: 45. Role and Responsibilities of CDM 51:53
  • 46: 46. Medical Device Trials 51:07
  • 47: 47. Clinical Research Q and A 51:54
  • 48: 48.Clinical Data Management Q and A 1:04:50
  • 49: 49. Clinical Research CDM Fundamental Q and A 1:00:17
  • 50: 50. Working with CROs and SOPs 45:34
  • 51: 51. CDISC - Part 1 22:31
  • 52: 52 CDISC - Part 2 33:15

Clinical SAS - Course Syllabus

1. SAS Clinical Research Overview

2. Historical and Ethical background of Clinical Research and ICH-GCP Guidelines

3. Essential Documents in Clinical Research

4. Drug Development

5. Clinical Trial Process and Roles

6. Clinical Trial Design

7. Clinical Trial Monitoring

8. Glossary of Clinical Research Terms

9. Responsibilities of Sponsor

10. Site Selection and Responsibilities of Investigator and CRC

11. QA and QC Audit and Inspection

12. Non-Compliance, Fraud and Misconduct

13. 21 CFR part 11

14. Protocol Understanding

15. Clinical Data Management

16. Protocol Assignment

17. CRF Design and Format

18. CRF Design and Format demo

19. Clinical Data Standards

20. CDM Study Start Up

21. CDM - EDC Setup Concept

22. CDM - EDC Study Conduct Concept

23. CDM - EDC Study Conduct Discrepancy Management

24. CDM - Discrepancy Management

25. Data Management Plan

26. Project Management for Data Manager

27. Vendor Selection and Management

28. Edit Check Design Principles

29. EDC Study Closeout

30. CDM Study Closeout

31. CRF Completion Guidelines

32. Database Validation and Programming

33. Laboratory Data Handling

34. External Data Transfer

35. Patient Reported Outcome

36. Investigator Meeting

37. Metrics in CDM

38. Assuring Data Quality

39. Measuring Data Quality

40. Safety Data Management

41. Safety Data Reconciliation

42. Medical Coding

43. Clinical Data Archiving

44. Data Entry and Processing

45. Role and Responsibilities of CDM

46. Medical Device Trials

47. Clinical Research Q and A

48. Clinical Data Management Q and A

49. Clinical Research CDM Fundamental Q and A

50. Working with CROs and SOPs

51. CDISC - part 1

52. CDISC - part 2

The target audience for the SAS Clinical course includes professionals and students who work in or aspire to enter the pharmaceutical, biotechnology, medical device, and clinical research industries. Here’s a breakdown of the key groups:

• Clinical Research Associates (CRAs)

• Clinical Data Managers

• Biostatisticians

• Clinical Trial Analysts

• SAS Programmers working on clinical trials (SDTM, ADaM, TLFs)

• Statistical Programmers involved in CDISC standards

• Medical Writers needing data insights

• Regulatory Affairs Specialists dealing with submissions (e.g., FDA, EMA)

• Pharmacovigilance Professionals analyzing safety data

• Graduates/Postgraduates in Biostatistics, Life Sciences, Pharmacy, or Public Health

• Career switchers aiming for clinical SAS programming or data analysis roles

• CDISC standards (SDTM, ADaM)

• Clinical trial data processing

• Macro programming for clinical studies

• FDA/ICH regulatory compliance

• Creating tables, listings, and figures (TLFs)

This course is ideal for those looking to work in clinical data analysis, regulatory submissions, or clinical trial reporting using SAS.

Passion to learn and succeed!

• Clinical SAS Programmer

• SAS Programmer Analyst

• Clinical Data Analyst

• Statistical Programmer

• Biostatistician

• Clinical Programmer

• CDISC SAS Programmer

• Data Manager

• Clinical Trials Programmer

• Regulatory Submissions Programmer

• Lead SAS Programmer

• Principal Statistical Programmer

• Statistical Analyst

• Clinical Research Associate

• Clinical Informatics Specialist

• Data Analyst

Currently there are no Q&As for this course. Be the first to ask a question.