Companies in regulated spaces have to be able to quickly respond to changing market needs, and they must do so in a way that ensures compliance with governing bodies. For these businesses, the decision of what to keep in-house vs. what to outsource is even more critical and sensitive in nature.
This paper discusses how to use the principles of root cause analysis in statistical programming and reporting for CAPA. Download the paper now.
A total error approach can assist with lab data analysis, clinical trials, or the testing of new drugs in the pharmaceutical industry. Learn more here.
In this paper, Data Visualization: The Epilepsy Story, we tell the story of epilepsy based upon the exploratory analysis and visualization of data for clarity.
Measuring the health of a Sponsor's clinical programming FSP model involves establishing the right KPIs from the start. Read our post to learn which KPIs matter
The purpose of this article is to provide insight into the comparison of dissolution profiles using f2 analyses to characterize drug products more precisely.
For programmers who analyze clinical trial datasets in pharma and biotech industries, the Standard Data Tabulation Model (SDTM datasets) is valuable. Learn more.
PhUSE is hosting the event, “Utilizing Risk-Based Monitoring to Identify and Mitigate Risk While Ensuring Patient Safety, Data Quality and Integrity”