#FutureReadyHealthcare
American multinational applies NLP and automates labeling operations
Challenges
Capacity constraints to manually maintain local label compliance against reference label/Company Core Data Sheet (CCDS)
Low accuracy from manual content comparison between the Company Core Data Sheet (CCDS) and related Prescribing Information (PI)/Summary of Product Characteristics(SmPC) labels
The Solution
Indegene deployed a team of regulatory experts and AI programmers in flexible offshore-onshore model to monitor US and EU regulatory requirements. Using NLP-based content comparator in Indegene's proprietary product, NEXT Label Lifecycle Automation, we deployed highly efficient automation on client's labeling content. NLP-based system confidence scores identified text mismatch between CCDS, to PI and evaluated fuzzy logic similarities between PI and patient leaflets which automated editorial and proofreading capability for labeling operations.
Outcomes
Indegene was able to fast forward the company’s vision of improving access by bringing in automation to their local label compliance requirements for pharmaceuticals
Using NLP, we were able to showcase improved accuracy of content across markets, and reduced turnaround times
>85%
Accuracy over manual
40% ↓
Turnaround time
~90%
Accuracy in content comparison
