A global pharma company asked Euretos to help in finding novel indications, with a focus on rare diseases, for a number of drugs already on the market. They had already created an initial list of indications which they wanted to assess but were also looking for novel indications with limited mention in literature but strong underlying biological data to support the target association. There was also severe time pressure and they wanted to conclude the initial selection process in 4 weeks.

Especially with the very short timescales, there were significant challenges including:

• There are potentially thousands of indications to consider; how do you compare all these options and select the best ones? 
• How do you avoid literature bias to find promising indications that have good underlying biological data but little mention in literature? 
• How do you enable your disease experts to evaluate a potential indication, especially in new therapeutic areas where you may lack prior experience and expertise? 

Based on its many collaborations with leading pharma and biotech companies on indication selection, the company asked Euretos to support them in this endeavour.

“The unique combination of novel predictions from the Euretos computational disease models with the ability for domain experts to assess these independently in the Euretos AI platform proved very effective. The company was able to build within a very short time frame the confidence necessary to decide which indications to move forward for further development.”

For the project, Euretos was able to draw on it’s unique, AI-powered computational disease models that predict truly novel indication candidates for a target by:

• Focusing on genetic associations and biological networks data, minimising potential literature bias
• Taking into account target interaction networks to assess yet unexplored disease associations
• Integrate the companies proprietary target-specific data in order to obtain the most relevant predictions

We knew from many previous projects that the ability to assess these predicted indications by target or disease experts is crucial to move a candidate forward in the selection process. We therefore provided the companies domain experts access to the Euretos AI Platform to independently evaluate the predicted indications through: 

• An AI-integrated knowledge base which harmonises all supporting evidence from biomolecular databases, publications and patents 
• Easy-to-use applications to evaluate all relevant aspects of target-indication involvement
• A collaborative research environment which connected disease experts and Euretos research consultants. 

The unique combination of novel predictions from the Euretos computational disease models with the ability for domain experts to assess these independently in the Euretos AI platform proved very effective. The company was able to build within a very short time frame the confidence necessary to decide which indications to move forward for further development.