ClipLab can give you the Clinical SAS Training you need to help your career take off.
If you are looking to begin a career in clinical research,
knowing SAS can make the difference between getting hired and not getting hired. In the tech world, "hard skills" are in and "soft skills" are out. Getting clinical SAS training will undoubtedly help your career take off in the pharma and biotech industries.
Why is SAS Important?
SAS is at the core of analysis dataset development, analysis dataset validation, report generation, graph generation, and dataset merging for PK analysis. Clinical SAS Training is valuable for the following:
* Analysis Dataset Development: Data is at the heart of research, and developing analysis datasets is the first part of clinical trials analytics. Developers write SAS code to create analysis datasets from raw clinical data.
* Analysis Dataset Validation: Accuracy of data is absolutely essential in clinical research. Independent validators create their own code in SAS and compare the analysis dataset they come up with to the one obtained in the study to validate the data.
* Report Generation: A report can be published and share a study's results with other scientists and officials. Report generators will use given analysis datasets, mock shells, and guidelines to create their own summary reports and listings to interpret the data and make inferences from the statistics and clinical data. They write these reports in SAS code.
* Report Validation: As with analysis datasets, reports must be validated. Independent report validators hired by a study write SAS code from analysis datasets and RTF (Rich Text Format) Reports.
* Graph Generation: A graph helps you format and visually analyze your data. They are particularly helpful for the people who will read your report, usually regulatory officials, because they will be able to see from the graph broad trends of data. SAS is used to generate error bar graphs for the PK data endpoint and the percent change form baseline plot (formula Mean+/- SE) for a lab test.
* Merging of Datasets for PK Analysis: PK, which stands for Pharmacokinetic, analysis integrates PK concentration data and the datasets created from this data in the database. The data is usually factors such as blood collection, demographics, dose administration, and vital signs. You can create a PK analysis dataset, based on the raw PK datasets and clinical datasets, using SAS code.
Once you receive clinical SAS Training, you will be able to perform all of these tasks with ease!
