Analyze Scientific Content at Scale With Intelligent  Literature Monitoring

Intelligent Literature Monitoring (ILM) with Integrated Artificial Intelligence Case Study

Transforming literature search and publication planning with Artificial Intelligence

Intelligent Literature Monitoring (ILM) is a new approach to systematic literature searches around therapeutic domains.

ILM uses Artificial Intelligence (AI) and its subset discipline Natural Language Processing (NLP). It extracts valuable insights from the world's largest set of open-access scientific sources, as they are being published, into one platform.

Case Study Objective:

Sorcero, MEDiSTRAVA, Coherus, and Moderna aimed to demonstrate the benefits of transforming literature monitoring from a manual report-based process into an intuitive, semi-automated, AI-driven process.

Methods:

We assessed two approaches to continuous literature monitoring: 

1. Manual search and output
2. Semi-automated search, with AI integration and digital output, applied across search scenarios producing high (>250) and low (<100) volumes of results.

ILM was performed using the Sorcero LI Platform and the BioBERT language model against identical corpora.

We compared:

• Man-hours
• Sensitivity
• Specificity
• Versatility
• Depth of insights
• User experience

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