SAS is widely used in clinical trial data analysis in pharmaceutical, biotech and clinical research companies. SAS programmers play an important role in clinical trial data analysis. SAS programmers implement the analysis methods on the collected data and provide the study summary tables, data listing and graphs to the statisticians. SAS programmers work closely with statisticians and data managers. They provide the link between raw data and the analysis.
This comprehensive course provides extensive training in SAS for clinical trial data analytics and statistical modeling, covering Base SAS and Advanced SAS for Global Certification, as well as specific modules on ADaM, TLF, and SDTM. Students will learn essential concepts, techniques, and best practices for clinical trial data management, analysis, and reporting using SAS software. The curriculum is aligned with industry standards and designed to prepare students for roles in pharmaceutical, biotech, and healthcare industries involved in clinical research and development.
COURSE CURRICULUM
- Drug Discovery and Clinical Research
- ICH GCP (Good Clinical Practice)
- 21 CFR Part 11 _ Electronic Records, Electronic Signatures
- Statistical principles for clinical trials (ICH E9)
- Standard operating procedures (SOP’s)
- Base SAS & Advance SAS
- Protocol
- aCRF (Annotated case report form)
- Statistical Analysis Plan (SAP)
- CDISC Standards (SDTM, ADaM)
- TLFs (Tables, Listings, and Figures)
- Training on Oncology project
BIOSTATISTICS
- Introduction to Biostatistics – Clinical Applications
- Frequency Distribution of Clinical data
- Clinical Data Presentation
- Measures of Centering Constants
- Measures of Dispersion
- Normal Distribution
- Null Hypothesis / Alternate Hypothesis
- p – Value Interpretation
- Sampling Variation
- Probability Concepts In Clinical Trials
- t-Test – Pharma Applications
- Chi Square test – Adverse Event Analysis
- Correlation & Regression – Estimation Analysis
- ANOVA – Efficacy Analysis
- Randomization
OTHERS
- Daily Tasks
- Certification Guidelines
- Sample Questions
- Resume Preparation
- Mock Interviews
- Group Discussions
- Personality Development