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  • Preclinical & Laboratory Foundations Learning Path
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Preclinical & Laboratory Foundations Learning Path - courses at £199

About

Biostatistics - SAS Programming for Clinical Trials training provides the knowledge and practical skills required to manage, analyse, and report clinical trial data using SAS, the industry-standard programming platform widely used in pharmaceutical, biotechnology, and clinical research environments. It equips learners with a strong foundation in SAS programming concepts, clinical data standards, statistical reporting, data manipulation, quality control, and regulatory-compliant data analysis practices.
This Biostatistics - SAS Programming for Clinical Trials Course & Certification covers SAS programming fundamentals, DATA step processing, PROC procedures, clinical data management, CDISC SDTM and ADaM standards, dataset merging and transformation, SAS macro programming, generation of Tables, Listings and Figures (TLFs), debugging techniques, quality control methods, and clinical trial reporting workflows. Upon successful completion, learners receive a certification demonstrating their understanding of SAS programming principles and their application in clinical research and regulatory submission environments.

Who Should Enrol?

  • Clinical Data Managers and Clinical Data Coordinators
  • Biostatisticians and Statistical Programmers
  • Clinical Research Associates (CRAs) and Clinical Trial Professionals
  • SAS Programmers seeking experience in clinical trials
  • Pharmaceutical, Biotechnology, and CRO Personnel
  • Regulatory Affairs and Clinical Operations Professionals
  • Quality Assurance and Compliance Professionals involved in clinical research
  • Students, Graduates, and Professionals seeking a career in Clinical SAS Programming and Biostatistics
📢 Every purchase also includes our FREE companion SAS Programming for Clinical Trials eBook, designed to help you apply principles in real-world clinical research settings.

What you will learn

Understand the principles of SAS programming and its application in clinical trials, biostatistics, and regulatory submissions.

Learn how to create, manage, transform, and analyse clinical research datasets using DATA steps, PROC procedures, and SAS functions.

Develop knowledge of CDISC SDTM and ADaM standards, dataset merging, macro programming, statistical reporting, and the generation of Tables, Listings, and Figures (TLFs).

Gain understanding of data quality control, debugging techniques, traceability, regulatory expectations, and best practices for producing accurate, reproducible, and submission-ready clinical trial analyses.

Course Syllabus

  1. What clinical SAS programming is and why it is in demand
  2. Who this course is for and the no-prior-SAS premise
  3. The running ORION-3 practice study (SDTM DM/AE/LB, ADaM ADSL)
  4. Getting SAS access (SAS Studio / OnDemand for Academics / University Edition)
  5. How the hands-on exercises work
  6. Course roadmap and learning outcomes
  7. Boundary and prerequisites

  1. Touring SAS Studio: program, log and results
  2. Libraries and the LIBNAME statement; WORK vs permanent
  3. Two-level names and inspecting data with PROC CONTENTS
  4. DATA vs PROC; statements, semicolons and comments
  5. Datasets, observations, variables and missing values
  6. Reading the log: NOTE, WARNING, ERROR
  7. Hands-on: assign a LIBNAME and PROC PRINT the DM dataset

  1. The DATA step flow: compile/execute, PDV and the implicit loop
  2. Reading data with SET, INPUT and INFILE
  3. Assignment, operators and SAS dates (INTCK/INTNX/YRDIF)
  4. Functions: SUBSTR, SCAN, PUT/INPUT, SUM
  5. IF-THEN/ELSE, SELECT and the subsetting IF
  6. WHERE vs IF; KEEP/DROP/RENAME
  7. Handling missing values in derivations
  8. Hands-on: derive AGE from DOB and visit date and flag AGE>=65

  1. PROC PRINT: VAR, WHERE, BY, ID, SUM
  2. PROC SORT: BY, DESCENDING, NODUPKEY, DUPOUT=
  3. PROC FREQ: one- and two-way tables, /LIST and /MISSING
  4. PROC MEANS/SUMMARY: statistics keywords, CLASS, OUTPUT OUT=
  5. BY vs CLASS; counting subjects vs events
  6. Categorical to FREQ, continuous to MEANS
  7. Hands-on: FREQ of AE by arm and MEANS of a lab value by visit

  1. Why CDISC: SDTM, ADaM, Controlled Terminology, define.xml
  2. SDTM structure: domains, --TESTCD/--SEQ and USUBJID
  3. The DM, AE and LB domains and their key variables
  4. ADaM principles: ADSL (subject-level) and BDS (PARAMCD/AVAL)
  5. Population and analysis flags (SAFFL, ITTFL, ABLFL)
  6. Traceability SDTM to ADaM
  7. Hands-on: subset DM, inspect AE and build ADSL-style ITTFL/AGEGR1 flags

  1. SET: concatenation and interleaving
  2. MERGE ... BY: match-merge and IN= flags
  3. One-to-many merges and emulating join types
  4. Pitfalls: unsorted input, many-to-many, variable overwrite
  5. PROC SQL joins as an alternative
  6. PROC TRANSPOSE: long to wide and back
  7. Hands-on: merge DM with AE by USUBJID and derive a treatment-emergent AE flag

  1. Why macros; the two-stage macro processor
  2. Macro variables, &name and %LET
  3. Automatic macro variables (&SYSDATE9, &SYSLAST)
  4. %MACRO/%MEND with parameters; %IF and %DO
  5. CALL SYMPUTX and double-quote resolution
  6. Debugging with SYMBOLGEN, MPRINT and MLOGIC
  7. Hands-on: write %summarize(param=) to run PROC MEANS for any analyte

  1. TLF in clinical reporting; SAP, shells and Table 14.1.1
  2. PROC REPORT: COLUMN, DEFINE and COMPUTE
  3. PROC TABULATE basics
  4. Building a demographics Table 1 and subject listings
  5. ODS RTF/PDF output; titles, footnotes and big-N headers
  6. Formatting, rounding and zero-count categories
  7. Hands-on: build a demographics summary and an AE listing to RTF

  1. Anatomy of the SAS log; NOTE vs WARNING vs ERROR
  2. Classic messages: uninitialized, MERGE repeats, conversions
  3. Missing-value maths and 0-observation red flags
  4. Triage: read the first error first
  5. Defensive programming: PUTLOG, assertions, obs counts
  6. Validation, double-programming and PROC COMPARE
  7. Hands-on: given a broken program and its log, find and fix the errors

  1. Synthesis: the junior clinical SAS programmer competency checklist
  2. Where to keep practising (ORION-3 datasets, SAS access)
  3. Glossary - SAS and CDISC key terms
  4. References - SAS docs, CDISC SDTMIG/ADaMIG, PHUSE, ICH E9
  5. Final Evaluation - module assessments and final exam
  6. Boundary note and next steps
  7. course completion

  1. 📘 Bonus: SAS Programming for Clinical Trials eBook (Free with purchase)

Course Benefits

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Free eBook

Get our exclusive eBook with every purchase - a complete companion guide to the course, yours to keep forever

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CPD Points

Gain Continuing Professional Development (CPD) Points, accredited by The Faculty of Pharmaceutical Medicine of the Royal College of Physicians of the United Kingdom. These can be used to count towards the distance learning element of any scheme that comes under the umbrella of The Academy of Medical Royal Colleges or any other scheme for which there is mutual recognition.

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Certification

Receive a personal certificate to show your subject knowledge on course completion.

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Affordable

You get excellent value through our cost-effective prices. We can also offer you group discounts on larger purchases.

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Flexibility

The course saves you time through the convenience of online availability. This lets you complete the interactive course at your own comfort.

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Keep Up to Date

You will stay up to date with CDISC standards (SDTMIG and ADaMIG), Controlled Terminology and ICH E9 conventions, and with Base SAS programming practice as used in clinical trials, as our training courses are constantly monitored, reviewed and updated.

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Learn from Industry Experts

The course content has been developed by experienced clinical SAS programmers and biostatisticians to ensure that learners can write, debug and validate real clinical-trial programs at the bench.


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