Clinical Data Interchange Standards Consortium (CDISC) is a global not-for-profit organization that focused on the interchange of clinical information within the pharmaceutical market. Categorically, CDISC is very aligned with the desiderata of clinical tribulation data exchange as it relates to clinical research workflow.
The goal of CDISC is to catalyze the information permeate pre-clinical and clinical research process, from study protocol and sundry data amassment to analysis and reporting through regulatory submission and electronic data archive. CDISC mainly consists of the following:
- Study Data Tabulation Model (SDTM)
- Analysis Data Model (ADaM)
- Operational Data Model (ODM)
- Laboratory Data Model (LAB)
- Case Report Tabulation Data Define Designation (CRTDDS) – Define.xml
- Protocol Representation (PR)
- Tribulation Design Model (TDM)
- Clinical Data Acquisition Standards Harmonization (CDASH)
- Terminology
Benefits of implementing CDISC standards?
- Fostered efficiency
- Complete traceability
- Enhanced innovation
- Amended data quality
- Facilitated data sharing
- Abbreviated costs
- Incremented predictability
- Streamlined processes
Involvement of SAS Programmers in Clinical Trials
The role of Clinical Trials SAS Programmers vary from simple SAS programming to engendering the analysis data and the table, listing, and graphs. The following are examples of various roles for clinical trials SAS programmers:
- Edit Check Programming
- eCRF annotation
- Engendering the derived data sets
- Engendering the tables, listings, and graphs.
- Importing the external data and converting to SAS data sets.
The implementation of CDISC standards requires more than programming from SAS programmers. The role of SAS programmers in CDISC depends on the job description in each company, but SAS programmers can be exposed to the following areas in the CDISC environment other than SAS programming adeptness.
- SDTM – Electronic Data Capture (EDC) and Electronic Case Report Form(eCRF) annotation
- ADaM – Statistics
- ODM – XML programming cognizance
- LAB – Conversion of aeonian data to SAS data set format
- Define.xml – Metadata of SDTM and ADaM and XML programming cognizance
- PR – Protocol
- TDM – Statistical Analysis Plan (SAP) and SDTM
- CDASH – EDC system
- Terminology
As indicated above, each standard requires different skills and backgrounds from SAS programmers. Conventionally SAS programmers get involved in developing SDTM and ADaM. SDTM can be developed from raw data from EDC by SAS. So, SAS programmers need to understand the following:
- Electronic Data Capture (EDC) system (ex. Oracle Clinical, Apprise, ClinTrial, etc.)
- Database Structure
- Domains or tables
- Data Type – numeric, character, timing, etc.
- Conversion of data to SAS format
- SDTM Concepts
ADaM is customarily derived from SDTM. The rudimentary principles of ADaM are analysis readiness, traceability, and the link to metadata. In order to provide traceability and metadata, SAS programmers need to understand SDTM. To engender analysis-ready ADaM, SAS programmers need to understand the statistical method for some of the efficacy analysis.
SAS programmers withal need to understand the exact SAS statistical procedures for analysis such as proc
denotes, proc freq, proc ttest, proc glm, proc npar1way, proc reg, proc commixed, proc life test, proc phreg, proc logistics, and so on.
Advantages for SAS Programmers
There will be more data in the health care industry to analyze because all the data including the clinical trial data become standardized. It will be much easier to obtain and analyze the data and SAS will provide the best solution. SAS won’t be the only software, but simply one of the best out there especially in the data manipulation and analysis. Due to the current involvement in the clinical trial, the role of SAS programmers will expand. Because SAS programmers are the last group in the CDISC path, we will be in the ideal position to review the final output as well as all the CDISC clinical trial processes. The SAS programmers’ involvement in the CDISC clinical trial is likely to expand. There will be more opportunities for SAS programmers who have CDISC experiences. Rather than starting from scratch, some sponsors will outsource CDISC implementation and manage that process. Therefore, SAS programmers who have extensive CDISC experiences will have more opportunities as consultants as well as project managers.
Disadvantages for SAS Programmers
There will be more software package to analyze CDISC data adjacent to SAS. Because CDISC is a standardized form, it is much more facile to import the data into the software for the automatic analysis. For example, JMP® Clinical apperceives. CDISC data and automates the analytics and reporting of the safety data albeit the users do not have CDISC cognizance. Consequently, some of SAS programming could be superseded because of the emergence of other CDISC concrete software.
Because of the emergence of ODM, there will be a great demand in XML data format. XML format data will be used in data transfer more. CDISC is a component of electronic clinical tribulation rather than paper, so the pace of CDISC clinical tribulation will go more expeditious, so SAS programmers do not have as much time as afore. CDISC is the standardized process, so SAS programmers need to work in a more structured and standardized setting than before.
Things to consider
The pharmaceutical industry heavily depends on SAS programming for data manipulation and statistical analysis. But, the FDA relishes being neutral in terms of vendor cull. XML is an open data model and vendor-neutral so even FDA discusses the possibility to accept SDTM and ADaM by XML format not by SAS XPORT format in the future. It is not sure if the transition from XPORT to XML will ever transpire because of the nature of clinical data, but it is sure that XML format data will be utilized more. It will be a great advantage if SAS programmers ken about XML data format.
Since all the clinical data is standardized, it will be more facile to integrate the clinical data. So, there will be more opportunities in data mining. The company and agencies will endeavor to analyze the clinical data across different clinical tribulations and therapeutic areas. CDISC is a component of drive that all the data should be in the standardized form, so CDISC will follow the direction that its data can be merged into other standardized data such as HL7. So, SAS programmers who have the faculty to understand the different data structures and formats will be able to take full advantage of the standardization movement in health care data.
For example, unlike the mundane tabular structure in the clinical tribulation such as SDTM and ADaM, the ODM XML data structure is hierarchical. In additament, SAS programmers will spend more time developing structured codes such as CDISC concrete macros rather than custom SAS programming. SAS programmers should have a clear understanding of CDISC for FDA submission to evade the delay or repudiation by the FDA because the submission does not meet FDA prospects.
Conclusion:
CDISC will present the disadvantages and advantages to SAS programmers. If SAS programmers want to prosper in the CDICS environment, they require to understand the purport of CDISC implementation and each critical path and furthermore, learn the compulsory skills. In additament, the current CDISC is not a final product. It will keep evolving. It is not sure how CDISC will evolve, but if SAS programmers are open to changes and are able to acclimate to the incipient changes and skills, SAS programmers will be able to take full advantage of it as CDISC progresses.
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