Featured Editorial
AI, Data Integrity, & The Life Sciences: Let’s Not Wait Until Someone Dies
 
By Kip Wolf, Tunnell Consulting, @KipWolf

Data integrity and data quality are critical success factors for artificial intelligence (AI) and machine learning (ML) solutions in life sciences. Simply performing computer system validation or managing computer systems under CGMP conditions is not enough to ensure data integrity and data quality for data sets where AI/ML is intended to be applied.

Industry Insights
How To Drive Down Laboratory Operating Costs With SaaS
Article | Dassault Systemes Americas

Explore best practices in SaaS selection and how its incorporation into laboratory practices enable organizations to focus on core competencies while utilizing best-of-breed software.

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Strategies For Protein Purification Handbook
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