Scroll Top
logo averbis information discovery

Systematic Literature Review

Reduce time to market!

Systematic Literature Reviews are an integral part of every successful pharma companies R&D efforts. Currently SLR’s are performed manually in a time and resource consuming process. On the one hand this occupies highly educated employees on routine tasks, not maximizing their full potential. On the other hand, SLR’s are associated with strict time constraints creating a need for the shortest solution of the highest quality.

Bild SLR

Real-life example showing the time savings in one of our SLR projects with a major Pharma company.

Making SLR’s Fast and Reliable

With our combination of text mining and machine learning you can do exactly that, save time and effort with transparent and reproducible results. By training our classifiers on your unique classification behavior, the machine learning algorithm automatically classifies your chosen dataset and extracts the needed information. Additionally, it automatically generates rules for identifying PICOS based on the unique dataset at hand. These results can then be easily exported into your systems through open API’s.

This allows you to:

Save up to 75% of time and costs

Get more accurate results using NLP and ML assisted classification

Significantly reduce the time of your SLR

Scientific Publications

A Systematic Review of Non-Small Cell Lung Cancer Clinical Trial Literature: Robots versus Humans

To find out how much time you could save and how accurate the results are check out the results of one of our SLR projects in a joint scientific publication with Roche. Click here to read more!

Machines As a Second Reviewer in Systematic Literature Reviews (ISPOR 2021)

Automation of Title and Abstract Screening: CAN Robots Replace Humans? (ISPOR 2021)

Find answers in your data

We would be glad to present our products to you and create a demonstration based on your selected data repositories.