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Global Pharma Leverages AI/ML and NLP to Transform Material Review Productivity ​

The Customer

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.

Challenges

  • Complex reviews/approvals, lengthy review cycles under and complex interdependencies​

    Manual and inconsistent review process, dependent on MLR reviewers and quality of commercial content submission, business deadlines​

The Solution

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

Outcomes

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

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