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.
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.
For the past 15 years, BioNetwork has brought together the most senior-level decision makers in pharma and biotech deal making (CEOs of BioTechs, VPs of BD from Big Pharma). Meet the right people and create the ideal partnerships.