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Data Analytics and Quality Intelligence for Non-IT
As the regulators push for “vigilant” oversight of our key processes, the natural response is to change our traditional approach to data review, visualization and monitoring, focusing on product quality assurance rather than ensuring simple “compliance” with GXP regulations. For non-traditional GXP software (data visualization/artificial intelligence), a new approach must be established to augment the previous “CSV” framework, which was not designed to evaluate risks in such systems.
Data Analytics and Quality Intelligence for Non-IT
As the regulators push for “vigilant” oversight of our key processes, the natural response is to change our traditional approach to data review, visualization and monitoring, focusing on product quality assurance rather than ensuring simple “compliance” with GXP regulations. For non-traditional GXP software (data visualization/artificial intelligence), a new approach must be established to augment the previous “CSV” framework, which was not designed to evaluate risks in such systems.