Data quality describes how well a set of data serves the purpose it represents. Data quality is measured by considering a series of characteristics including accuracy, validity, and consistency. The completeness and uniqueness of the data is also considered when assessing data quality.
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Over the past 25 years surgically dependent animal models have expanded from a small, almost niche area in pharmaceutical research to an important component of most research portfolios. In t...
The Chain of Custody in our labs is the unbroken link between the objects used in your research: your people, the animal models, the cell lines, reagents, compounds; the lab instruments and d...
DATE: February 26, 2019TIME: 9:00am PST, 12:00pm EST In an era of increasingly high-throughput, large-scale biology, with companies, government and non-prof...
Animal welfare is the most important issue in any in vivo laboratory. The ability to detect and intervene in cases where the conditions of animals may be deteriorating as well as the ability...
Digitalization has transformed virtually every industry, but it has been slow to gain traction within the preclinical phase of the drug development journey. Recent advances in digital vivariu...
DATE: February 5, 2019TIME: 9:00am PST, 12:00pm EST CloudLIMS.com is pleased to invite you to attend a complimentary webinar. The webinar focuses on the importa...
The biologics development process is fraught with risks from pre-clinical studies through clinical evaluation. Prominent among these risks are changes in the critical quality attributes of th...