Clinical programming

SAS Clinical Course

Master Base SAS, Advanced SAS, SAS SQL, Macros, clinical research theory, CDISC SDTM, ADaM, Define.XML, TLFs, validation, and clinical programming project work.

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Who this is for

Graduates and professionals targeting SAS Clinical Programmer, Statistical Programmer, or Clinical Trial Programmer roles
SAS programmers moving into clinical trial reporting and submission work
Clinical data professionals who need SAS, SDTM, ADaM, Define.XML, and TLF exposure

Outcomes

Build strong Base SAS and Advanced SAS programming foundations
Use DATA step processing, procedures, arrays, functions, ODS, SAS SQL, SAS STAT, and Macros
Understand clinical research theory, protocol data flow, SAP interpretation, and submission standards
Map and create SDTM domains, ADaM datasets, metadata, Define.XML, and validation outputs
Create tables, listings, and figures through clinical programming practice and project work

Tools and topics

Core concepts and platforms covered through examples, assignments, and interview preparation.

Base SASAdvanced SASSAS SQLSAS MacrosSAS STATCDISCSDTMADaMDefine.XMLTLFsMedDRAWHODD

Course content

Structured modules for practical learning.

SAS Foundations

Introduction to SAS and SAS programming windows
SAS libraries and program structure
Global options, DATA step options, and global statements
DATA step statements including KEEP, DROP, LABEL, RENAME, WHERE, and LENGTH
Informats, formats, program objectives, and coding discipline

DATA Step Processing and Data Handling

DATA step processing flow and automatic variables
Combining, modifying, and updating SAS datasets
Retain statements, control statements, logical variables, and conditional processing
Input styles, INFILE, FILE, pointer controls, and raw data handling
Arrays, SAS functions, and practical dataset transformations

SAS Procedures and Reporting

ODS concepts and output delivery
PROC PRINT, SORT, CONTENTS, APPEND, TRANSPOSE, COMPARE, OPTIONS, DATASETS, COPY, FORMAT, IMPORT, EXPORT, CPORT, CIMPORT, PRINTTO, and DELETE
PROC TABULATE, REPORT, CHART, GCHART, PLOT, GPLOT, and Graph-N-Go concepts
Clinical listing and summary report preparation
Programming practice with reusable report patterns

SAS STAT, SQL, and Macros

PROC UNIVARIATE, MEANS, FREQ, CORR, REG, ANOVA, GLM, RANK, and FORECAST
SAS SQL create, insert, alter, update, select, where, order by, group by, having, and distinct
SQL functions, options, joins, set operators, integrity constraints, and pass-through concepts
SAS Macro variables, macro programs, parameters, and reusable code
Advanced SAS programming patterns used in clinical data work

Clinical Research Theory for SAS Programmers

Drug development, clinical trial phases, approval process, and submission workflow
ICH-GCP E3, E6, E9, 21 CFR Part 11, protocol, ICF, CRF, and annotated CRF concepts
Electronic data capture workflow and SAP interpretation
Clinical trial designs, reporting requirements, and analysis flow
MedDRA and WHO Drug coding concepts for clinical datasets

SDTM Mapping and Domains

CDISC standards and SDTM implementation guide overview
SDTM fundamentals, mapping, metadata specifications, and validation
CDISC variable types, core variables, timing variables, custom domains, and supplemental qualifiers
Special purpose domains DM, CO, SE, and SV
Interventions CM, SU, EX, PR; events AE, CE, DS, DV, HO, MH; findings DA, PE, VS, LB, IE, QS, RP, SS, EG

ADaM, Define.XML, and Validation

ADaM implementation guide and mapping rules
ADSL and Basic Data Structure datasets
ADaM metadata specifications and dataset creation
Define.XML for SDTM and ADaM
FDA submission standards, validation checks, issue resolution, and documentation

TLFs and Clinical Programming Projects

Tables, Listings, and Figures concepts
TLF generation from SAP and analysis datasets
Standard SDTM macros and reusable programming approach
Clinical programming project with SDTM, ADaM, Define.XML, and TLF outputs
Interview-focused project review and practical programming scenarios

Potential recruiters

Training connected to pharma, CRO, healthcare data, and technology roles.

FAQs

SAS Clinical questions

Quick answers for candidates evaluating this course before applying.

Who is the SAS Clinical course best for? +

Graduates and professionals targeting SAS Clinical Programmer, Statistical Programmer, or Clinical Trial Programmer roles SAS programmers moving into clinical trial reporting and submission work Clinical data professionals who need SAS, SDTM, ADaM, Define.XML, and TLF exposure

What will I learn in SAS Clinical? +

Build strong Base SAS and Advanced SAS programming foundations Use DATA step processing, procedures, arrays, functions, ODS, SAS SQL, SAS STAT, and Macros Understand clinical research theory, protocol data flow, SAP interpretation, and submission standards Map and create SDTM domains, ADaM datasets, metadata, Define.XML, and validation outputs Create tables, listings, and figures through clinical programming practice and project work

Is this course instructor-led? +

Yes. Clini Data Curve courses are positioned as instructor-led live online training with recordings, assignments, assessments, resume preparation, mock interviews, and placement assistance.

How do I apply for this course? +

Use the Apply Now button or enquiry form to share your details and selected course. The team can guide you on batches, fit, and next steps.

Need guidance?

Talk to Clini Data Curve before choosing your course.

Share your background and career goal. The team can help you choose the right CDM, pharmacovigilance, SAS Clinical, CRA, medical coding, or clinical research path.

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