Transforming Pharma R&D

Situation

A top pharmaceutical company needed to leverage Key Opinion Leaders (KOLs) effectively to enhance drug discovery and drive consumer awareness. The process of identifying KOLs across English and Japanese publications was labor-intensive, slowing down R&D progress.

Challenge

The company faced critical obstacles:

• Language barriers requiring manual translation and expert input to identify Japanese publications.
• Inefficient search strategies lacking automation and scalability for cross-language queries.
• High effort, making it difficult to develop and maintain Japanese-specific search strategies

Approach

Mu Sigma harnessed AI-driven Natural Language Processing (NLP) and machine learning to create a unified, automated search system:

• Developed word embeddings using the Universal Medical Language System for English and Japanese, enabling precise understanding of word contexts across languages.
• Applied the K-Nearest Neighbor algorithm to retrieve Japanese articles from English queries with contextual accuracy.
• Integrated the solution with existing search engines, eliminating translation delays and enabling seamless cross-language searches.

The advanced system enabled adaptive and intelligent search strategies, reducing manual effort and ensuring relevance in results.

Impact

• 17% increase in identified Key Opinion Leaders, accelerating R&D and outreach efforts.
• Significant reduction in effort for creating Japanese search strategies.
• A scalable system ready to expand to other languages, enhancing global research capabilities.