If you need SAS statistical programming services for clinical trials, contact us at firstname.lastname@example.org
Statistical programming is a crucial element in the development of a clinical trial.
More specifically, SAS statistical programming facilitates the handling of large amounts of clinical data, which can be cleaned and analyzed in a more efficient way.
- $The Importance of Statistical Programming in Clinical Trials
- $What Is SAS Statistical Programming?
- $What Are the Advantages of SAS Programming over Other Languages?
- $Are There Alternatives to SAS?
- $The Role of SAS Programmers in Clinical Trials
- $Qualifications of SAS Statistical Programmers
- $SAS Statistical Programming and CDISC
- $SAS Statistical Programming Services Offered by CROs
- $Sofpromed’s SAS Statistical Programming Services
Sponsors should ensure high-quality SAS programming capabilities when planning their clinical studies, either by having their own internal statistical programming team or by hiring these services from external companies.
The Importance of Statistical Programming in Clinical Trials
Statistical programming plays a vital role in the execution of clinical trials that are part of a drug development program.
Through the different stages of the drug development journey, statistical programming is used in clinical trials to tabulate, structure, analyze, and submit clinical data (e.g., for data reviews by regulatory authorities).
Statistical programming enables the organization, analysis, and reporting of the vast amounts of data generated during a clinical trial through the production of tables, figures and listings (TFLs).
By using statistical programming, the efficacy and safety data of a new drug can be effectively processed, evaluated and presented to regulators.
What Is SAS Statistical Programming?
SAS (Statistical Analysis System) is a programming language that has become a standard for data analytics of large volumes of data used in several different industries, including the medical, life science, and clinical research sectors.
The SAS programming language was created at the North Carolina State University, of the United States, by Anthony James Barr in 1960.
With SAS, statistical programmers can organize, tabulate, analyze and display —in a variety of charts and graphs— the raw data produced in a clinical trial to generate reports.
The SAS platform is very flexible and provides users with various means to manipulate, analyze, process, and report clinical trial data.
These great capabilities have positioned SAS as a leading global standard in the clinical research space.
What Are the Advantages of SAS Programming over Other Languages?
In a clinical trial, thousands of case reports with many data points each can be handled using platforms like SAS.
Additionally, SAS is a quite sophisticated and strong programming language, enabling programmers to execute extremely precise data manipulation and analysis as well as effectively present the data.
The SAS platform has been specifically designed to manage the volume of data and level of analysis needed to conduct large clinical studies.
Such an analysis is necessary for both a complete comprehension of a study’s findings and for effectively conveying those findings to pharmaceutical regulators.
SAS is used to process a large portion of the data that is annually reported to the FDA.
Are There Alternatives to SAS?
Yes. SAS is not the only technology available for clinical trial data analysis. One interesting alternative is R programming.
R is a language and environment for statistical computing and graphics. It provides a wide variety of statistical (e.g., linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques, and is highly extensible.
While SAS has been a programming language for clinical trials for years, there are also many benefits in using R.
Regulatory agencies do not prevent the use of R if the necessary validation and documentation are in place.
The Role of SAS Programmers in Clinical Trials
Statistical programmers write and review statistical analysis plans (SAPs), write and execute statistical programs, and analyze data sets according to the endpoints of the clinical trial protocol, the requirements of regulators, and the needs of sponsors.
Based on an SAP, statistical programmers create analysis files and reporting programs to produce the tables, figures, and listings required to produce a clinical study report.
They can also provide all programming needs, from the beginning to the end of a study, and continued monitoring, working seamlessly with a client’s staff and departments.
Qualifications of SAS Statistical Programmers
Statistical programmers who manage and analyze clinical trial data must have the following skills:
- Knowledge of statistics.
- Capacity to understand the clinical protocol and statistical methods.
- Ability to explore, query and analyze various data sets.
- High level of attention to detail, particularly in data entry and quality checks.
- As a general analysis tool in clinical trials, SAS proficiency is an essential requirement.
- Strong process, problem solving and analytical skills.
- Strong oral and written communication and interpersonal skills. Teamwork is necessary and plays an important role.
SAS Statistical Programming and CDISC
Before statistical programmers start generating lines of code in a clinical trial —particularly if the study data is to be submitted to the FDA—, SDTM (Study Data Tabulation Model) and ADaM (Analysis Data Model) specifications should be in place.
SDTM and ADaM are standards belonging to CDISC (Clinical Data Interchange Standards Consortium), which is an international organization that actively develops data standards for clinical research.
SDTM defines a standard structure for clinical trial data and for non-clinical study data tabulations, which are to be submitted as part of a product application to a regulatory authority such as the FDA.
On the other hand, ADaM defines dataset and metadata standards that support the efficient generation, replication, and review of clinical trial statistical analyses, and traceability among analysis results, analysis data, and data represented in SDTM.
Statistical programmers —as members of a clinical trial team— must be knowledgeable and follow CDISC standards in their work.
SAS Statistical Programming Services Offered by CROsMany clinical research organizations (CROs) with biometrics capabilities offer SAS programming services to biotechnology and pharmaceutical companies. These services typically include:
- Derived datasets.
- Database standardization for FDA submissions.
- SDTM and ADaM (annotated CRF, specifications, datasets)
- SAS programming of tables, figures, and listings (TFLs).
- Statistical reports.
- Validation/auditing of statistical outputs.