Back To Home :-
Header Description: It is very important to have a descriptive header inside a SAS program.
Header Description: It is very important to have a descriptive header inside a SAS program.
********************************************************************;
Program Name : name.sas
Program Name : name.sas
Author : chandravarma
Date last Modified : Apr 02 2010 :
Purpose/Description: Macro to add titles and footnotes
Input Files :
Output Files :
Macros Used :
Notes :
*********************************************************************;
2. Use proper indentation: New step (e.g. data step, proc sort, proc sql, etc) must always start with no indentation, first line in any step must have one tab indentation line and after if (or similar) statements we must have one additional tab indentation before the next if (or similar) statements.
3. UPCASE: Always use uppercase variable name and uppercase dataset names (including temporary datasets created in the program)
4. Dataset Names: Never use same dataset name for input and output datasets.
5. Comments: Comments are used to make your program easier to read and edit. Use the comment statement anywhere in a SAS program to document the purpose of the program. Nothing is more frustrating as to return to a program written months ago and not being able to figure out what you did and why you did it. Also, if someone else needs to look over your program, the task is made much easier, if the code is commented.
6. Create a Macro: If you think code will be used in multiple programs, create a macro. Do not try to do multiple things in one macro; chances are if something is broken in the macro, other programmer will not use that macro in their program.
7. Give some meaningful name to the temporary datasets.
+++++++++++++++++++++++++++++++++++++++++++++++++
CDISC and SAS
Why is the adoption of the CDISC standards important for the life sciences industry and what is SAS' relationship with CDISC?
A: The Clinical Data Interchange Standards Consortium (CDISC) is fundamentally changing the way information is being managed in the life sciences research industries, and is beginning to change the way the US Food and Drug Administration (FDA) reviews new drug applications.
Historically, most pharmaceutical organizations developed their own internal data standards, and associated processing, for managing research information. Each organization's unique approach to this information management process has done little to expedite the overall new drug development process, and in many ways has slowed it down - by requiring each organization to spend unnecessary effort acquiring, developing and implementing distinct processes. Furthermore, the submission of research data in nonstandardized formats makes it difficult for the FDA to develop standard, efficient, processes for new drug application reviews. In the case of urgent safety reviews when questions arise about a class of drugs (Vioxx, Celebrex, etc.), the integration of data from multiple research programs has proven to be a huge obstacle in analyzing any class-related effects.
These life sciences research companies have since recognized that they will distinguish themselves by the new science their organizations provide, and not by their proprietary information handling methodologies. So began CDISC. CDISC is a collection of research companies, services organizations and technology providers that have banded together to develop, distribute and implement a series of data standards to promote efficiencies and process improvements in the life sciences industries.
CDISC received major validation in July 2004 when the FDA announced the adoption of its Study Data Tabulation Model (SDTM) as the standard for submitting clinical trials data. The acceptance of CDISC's SDTM-based model means that now the FDA has a common data structure from which to review new drug applications. Common standards lead to common tools. Common tools lead to common processes, which ultimately result in faster and more accurate decisions regarding the approvals of new drug therapies. Although the FDA does not yet require all data to be submitted using the SDTM standard, its adoption of the standard is a key action that life sciences organizations will not ignore. In fact, Pfizer submitted the first SDTM data to the FDA in late 2004.SAS has been the standard for data transformation and analysis in the life sciences research industries for many years, and the required FDA data submission standard since 1999. That year, the FDA adopted the SAS transport format as the standard for delivering electronic data for FDA submissions.
SAS has a deep commitment to the life sciences industry in general and to CDISC in particular. Dr. Edward Helton, SAS chief strategist of regulatory and biomedical affairs, serves on the CDISC board of directors. SAS also supports CDISC as a corporate sponsor, and David Handelsman, SAS clinical research and development strategist, serves as a member of CDISC's industry advisory board. SAS experts also participate on CDISC data model teams.
While the move to a defined industry standard has been a slow process, CDISC is making significant strides in meeting this objective. As more organizations adopt the CDISC standards, processes will become more efficient and time to market (and cure) will be reduced.
A: The Clinical Data Interchange Standards Consortium (CDISC) is fundamentally changing the way information is being managed in the life sciences research industries, and is beginning to change the way the US Food and Drug Administration (FDA) reviews new drug applications.
Historically, most pharmaceutical organizations developed their own internal data standards, and associated processing, for managing research information. Each organization's unique approach to this information management process has done little to expedite the overall new drug development process, and in many ways has slowed it down - by requiring each organization to spend unnecessary effort acquiring, developing and implementing distinct processes. Furthermore, the submission of research data in nonstandardized formats makes it difficult for the FDA to develop standard, efficient, processes for new drug application reviews. In the case of urgent safety reviews when questions arise about a class of drugs (Vioxx, Celebrex, etc.), the integration of data from multiple research programs has proven to be a huge obstacle in analyzing any class-related effects.
These life sciences research companies have since recognized that they will distinguish themselves by the new science their organizations provide, and not by their proprietary information handling methodologies. So began CDISC. CDISC is a collection of research companies, services organizations and technology providers that have banded together to develop, distribute and implement a series of data standards to promote efficiencies and process improvements in the life sciences industries.
CDISC received major validation in July 2004 when the FDA announced the adoption of its Study Data Tabulation Model (SDTM) as the standard for submitting clinical trials data. The acceptance of CDISC's SDTM-based model means that now the FDA has a common data structure from which to review new drug applications. Common standards lead to common tools. Common tools lead to common processes, which ultimately result in faster and more accurate decisions regarding the approvals of new drug therapies. Although the FDA does not yet require all data to be submitted using the SDTM standard, its adoption of the standard is a key action that life sciences organizations will not ignore. In fact, Pfizer submitted the first SDTM data to the FDA in late 2004.SAS has been the standard for data transformation and analysis in the life sciences research industries for many years, and the required FDA data submission standard since 1999. That year, the FDA adopted the SAS transport format as the standard for delivering electronic data for FDA submissions.
SAS has a deep commitment to the life sciences industry in general and to CDISC in particular. Dr. Edward Helton, SAS chief strategist of regulatory and biomedical affairs, serves on the CDISC board of directors. SAS also supports CDISC as a corporate sponsor, and David Handelsman, SAS clinical research and development strategist, serves as a member of CDISC's industry advisory board. SAS experts also participate on CDISC data model teams.
While the move to a defined industry standard has been a slow process, CDISC is making significant strides in meeting this objective. As more organizations adopt the CDISC standards, processes will become more efficient and time to market (and cure) will be reduced.
Clinnovo is offering internships,Online courses,Post graduate diploma courses in Clinical Research,Clinical Data Management,SAS,Imaging analysis
ReplyDeletePh: 9912868928 04064635501 contact@clinnovo.com www.clinnovo.com
SAS® is widely accepted as the gold standard in determining safety and efficacy for clinical trials, and provides the
ReplyDeleteprimary mechanism for preparing data for these traditional clinical research analysis activities. Most traditional SAS
users in the pharmaceutical industry, however, are unaware of the broad range of SAS Business analytics that are widely
applied in other industries.
Very useful blog to learn sas clinical and very informative article thank you for sharing with us keep posting
ReplyDeletesas clinical training,sas clinical online training,sas clinical certification training,clinical sas training
Very informative blog and useful article thank you for sharing , keep postingsas training,sas online training, sas admin training,sas clinical training
ReplyDelete