mega888 apk Clinical SAS Programming | Clinical Trials
Course:  Clinical Trial SAS Programmer
Code:  CDAR
Virtual – Job Focused Self-Paced Online.
(Along Exercise Solutions – Role based tasks)
Post Training Assistance (PTA):
Includes resume support, narrative and mock.
Duration:  8 Weeks / 200 Hours
Online Access :
Qtech-Learning Management System (Q-LMS)
Fees : $1,633.14 CAD
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Course Description:

Qtech-Sol is a Clinical Science Training Provider. This course provides Foundation and Advanced learning to work as Clinical SAS Programmer / Data Analyst. The course emphasizes about role and tasks performed by SAS Programmer to Analyze and Report clinical data captured from clinical trials or post marketing surveillance (Pharmacovigilance data). The course curriculum is designed to give an edge to obtain job as Clinical SAS Programmer / Analyst with Pharmaceuticals, Biotech, Medical Device, Clinical Research Organizations (CROs) and with Research Clinics.

The Clinical SAS Programmer Research Data Manager will develop and manage core area of clinical data obtained thru clinical trials or post marketing surveillance. The person gets involved in SAS Efficiency Programming, Analysis and Validation of CRF data captured. Applies Good Clinical Practices, GxP regulations, Documentation using CRF Part 11 and SOP concepts, Performs Data Validation based on data types and protocol. participates to develop Statistical Analysis Planning and Hypothetical testing, Efficacy Data analysis using ISE and ISS concepts. Applies Clinical Data Interchange Standards Consortium (CDISC) concepts and creates datasets for reporting data as Tables Listing and Graphs (TLG). This program includes around 11 projects covering phase-wise clinical trial data towards Oncology, Ophthalmology, Cardiology and Central Nervous Systems (CNS) therapeutics areas. Also includes Pharmacovigilance and aggregate reporting concepts.

  • Admission Requirements:

    Recommended: An Associate or bachelor’s degree in Statistics, Biostatistics, Biotechnology, Economics, Computer Science, Engineering, Cognitive Science, Data Science, Machine Learning (ML), Artificial Intelligence (AI), Mathematics.

    The Ideal person must know SAS Modules (base, macros, Sql, stat and graphs). SAS software is required to participate in this programming course.

  • Learning Outcomes:
    The Benefit Student Gains

    The Benefit Student Gains

    • Upgrading the Knowledge required.
    • Better Resume Placement for promising jobs.
    • Low Investment, high learnings
    • Learn from Anywhere, Anytime at your pace.
    • Job and Title Based Tasks as followed and Practiced in industry
    • Applying Concept into Real-time (Policies, governance and tools)
    • Work on Role Based Tasks followed and Practiced in industry
    • Mocks and Narratives for Client Discussions
    • Readiness to work with limited support
  • Career Pathways

    The program objective is to help and meet the following career pathways, after completing this practicum program. Students can apply for below open job titles based on highest education background and prior experiences (if any).

  • SAS Programmer
  • Statistical Programmer
  • Programmer Analyst
  • Biostatistician
  • Clinical Data Modeler
  • Clinical Data Analyst
  • Data Scientist
  • SAS Data Analyst

The CDAR course is designed for individuals who are either SAS Certified or have advanced skills in SAS software functionality. This program is mostly recommended for experienced SAS programmers who are interested in career advancement in the clinical field. The course builds upon the concepts presented in the SAS Modules course. Emphasis is placed on how SAS is used in the clinical and pharmaceutical industries. The course comprises SAS Business and SAS Projects (Therapeutic Based Projects and Prototype Clinical Data). To ensure the candidates gain practical knowledge and hands-on skills in clinical data analysis and reporting in the industry, the teaching/learning and projects will be related to the clinical trials from phase I to phase IV. This includes various therapeutic areas, such as oncology, ophthalmology, cardiology and central nervous system. Related data analysis and reporting follow each phase of clinical trials.

36. Aggregate Reporting


Knowledge of the clinical domain:

1. Elementary SAS Concepts

2. SAS Efficiency Programming

3. Introduction to Clinical Trials

4. Types and Data in Clinical Trials

5. Clinical Trial Protocol Development

6. Elements of CRF Design

7. Electronic Data Capture (EDC)

8. Good Clinical Practices

9. Good Documentation Practices

10. Workflow Instruction Request

11. Documentation Templates

12. Introduction to Data Validation

13. Data-Based Validation

14. Protocol Based Validation

15. Basic of Statistics

16. Statistical Analysis Planning

17. Elements of Hypothesis Testing

18. Basic of Efficiency

19. Integrated Summary of Effectiveness (ISE)

20. Integrated Summary of Safety (ISS)

21. Clinical Data Interchange Standards Consortium

22. Preparing Analysis Data sets

23. Creating Tables Listing and Graphs (TLG)

24. Understanding Various Therapeutics Areas

25. Data-Based Therapy

26. Introduction to Phase I Studies

27. Oncology Project

28. Introduction to Phase II Studies

29. Ophthalmology Project

30. Introduction to Phase III Studies

31. Cardiology Project

32. Introduction to Phase IV Studies

33. Central Nervous Systems (CNS) Project

34. Introduction to Pharmacovigilance

35. Pharmacovigilance Reporting



1. About SA Institute

2. Introduction to SAS

3. Components of SAS Program and Code Writing

4. Running SAS Programs

5. Mastering Fundamental Concepts

6. Diagnosis and Correcting Syntax Errors

7. SAS Options

8. Types of Input Statements

9. SAS Format and Informatics

10. Using Advanced Input Techniques

11. SAS Date and Time

12. Subsetting, Combining and Sorting Datasets

13. Merging and Updating Data

14. Performing Conditional Processing

15. Performing Iterative Processing – Looping

16. Creating Customized List Reports

17. Arrays

18. Creating Enhancing List and Summary Reports

19. Creating Proc Tabulate


1. Fundamentals of Macros

2. Macro Application

3. Macros Program Structure

4. Macros Statements

5. Macro Variables

6. Macro Functions

7. Writing Macro Programs


1. Introduction to the SQL Procedure

2. Retrieving Data from a Single Table

3. Retrieving Data from Multiple Tablets

4. Creating and Updating Tables and Views

5. Programming with the SQL Procedure

6. Practical Problem-Solving with PROC SQL



1. Introduction to Statistics

2. Hypothesis Testing

3. One-Sample T-tests

4. Paired T-tests

5. Two-Sample T-tests

6. Analysis of Variance (ONE-WAY)

7. Analysis of Variance (TWO-WAY)

8. Linear Regression

9. Multiple Regression

10. Regression Diagnostics

11. Categorical Data Analysis


1. Producing Bar and Pie Charts

2. Enhancing the Output in the Graphs

3. Producing Plots

4. ODS (Output Delivery System)

5. Creating 3rd and Geographic Reports


Exposure to daily roles and responsibilities

1: Data-Based Validation

2: Protocol Based Validation

3: Elements of Hypothesis Testing (Pk, Pd and Dose)

4: Preparing Analysis Datasets and CDISC

5: Therapeutic Areas: Oncology Project

6: Therapeutic Areas: Ophthalmology Project

7: Therapeutic Areas: Cardiology Project

8: Therapeutic Areas: Central Nervous System (CNS) Project

9: Aggregate Reporting Process

10: SAS Efficiency Programming

11. Open CDISC Validator

  • Thanks to Q tech for helping me to get back to workforce within 2 months. The CDAR program task-based exercises, provided me insight of role performed in real-time allowing me to get started at job right away.

    Julee A – NYC

  • This SAS CDAR training gave me a real-time job experience. The learning process was gradual, and the tasks were very interesting and very useful for gaining hands-on experience. I learned more when compared to my previous knowledge before starting this course. All the tasks and scenarios were different, and it was a very good learning experience.

    Navya C – Dallas, Texas

  • The Clinical Data Oriented SAS Program (CDAR) topics were very helpful to rate me. Chapters were organized better for easy readability. Very nice self paced SAS classes.

    Nisha D M K, Philadelphia, PA

  • Category:
    Data Management
  • Duration:
    08 Weeks / 200 Hours
  • Price:
  • Language: