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Project-Title: Indication Prioritization using Artificial Intelligence (AI) and Machine Learning (ML).
“As Global Medical Advisor Oncology @ Boehringer Ingelheim – I have been assigned to lead a new project: “Indication Prioritization using Artificial Intelligence and Machine Learning”. The need for innovative technologies to accelerate pharmaceutical research and development has never been greater and Boehringer Ingelheim continues exploring technology approaches to complement our own expertise in research, development and translational medicine.
Innoplexus and its proprietary Knowledge Graph called Ontosight were seen as the right partner to look for solutions for the current project.
As expected, the Innoplexus’ Indication Prioritization approach with AI & ML was able to screen a far larger number of scientific publications, exclude potential “noise“ in a much shorter period versus traditional approach, delivering as well an unbiased and reliable result-set to support prioritize indications for a selected target.
We compared the results Innoplexus provided to our own traditional analysis and confirmed a substantial overlap in the results. It was indeed quite impressive to see that a machine-generated indication list matched well with our understanding. The advantage was to also have the result set ranked based on biological relevance, market potential as well as clinical feasibility, which is a limitation with our own analysis and the expert recommendations.
We also saw some positive surprises in Innoplexus’ results. For example, some new tumor types were highlighted, and this is where innovation was generated, I would say.
Being highly satisfied with this new approach of drug discovery, I have recommended Innoplexus to my colleagues in other teams responsible for other assets at Boehringer Ingelheim.”