Following the generation of successful results with the University of Michigan through the ACE program, Predictive Oncology is now actively calling for submissions for a...Learn more
Largest commercial biobank
The PeDAL team test the highest confidence drug-tumor pairing predictions (including hits and misses) against actual tumor samples from our proprietary biobank in our on-site wet lab.
Knowledgebase +
AI
AI technology leverages historical drug-response data (and first-party data provided by the partnering drug development team) to make an initial set of predictions of drug-tumor pairings.
Machine
Learning
Wet-lab testing results inform subsequent rounds of AI predictions. This iterative process repeats until the prediction results stabilize from round to round.
Identifying which molecules will work on which cancer types (and with which patients) can be like finding a needle in a haystack. PeDAL optimizes the early drug-discovery process by introducting the human element much earlier (via our biobank), than using AI to help test large experimental spaces more efficiently and with a higher degree of confidence.
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News & resources
This Executive Overview outlines the proof-of-concept study completed by Predictive Oncology to illustrate the power of our active machine learning (AI) platform paired with our...Learn more
In this white paper, Predictive Oncology (POAI) highlights a recent successful project in partnership with the University of Michigan Natural Products Discovery Core (NPDC) through...Learn more