Systematic Literature Review
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.
Real-life example showing the time savings in one of our SLR projects with a major Pharma company.
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:
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!
Find answers in your data
You may also be interested in