Client is one of the world’s leading global pharma organizations developing breakthrough products – in diagnostics, medical devices, nutrition, and branded generic pharmaceuticals to make a lasting impact on health in the more than 160 countries.

Content review process and cycle time transformation by applying AI/ML and Natural Language Processing through NEXT MLR Review Automation
Automated learning process to reduce average cycle time of content rejection prior to formal submission
Improved reviewer experience with machine assisted review to better track content versions, highlight and annotate incorrect and missing ISI statements
Increased process efficiency by incorporating spell check for US English, linked to Medical and Brand Dictionary
Improved Reviewer experience due to migration from manually reviewing material to machine assisted review thereby focusing on relevant issues
First level check performed by tools for claims/context thereby improving content quality upstream, reducing back and forth cycles and improving compliance
30%
Reduction in turn around time
95%
Machine capability to identify spelling errors
85%
Accuracy to identify claims and reference extraction