White paper validates highly reproducible drug response data. Results enable AI platform to model and predict patient outcomes on historical samples Leveraging more than 20...
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
A recent white paper released by Predictive Oncology’s highlights the challenge of late-stage clinical trial failures and the company’s ability to better navigate those obstacles...
Company expands AI/ML driven capabilities to pursue novel biomarker discovery to predict patient outcomes and drug response in oncology. Read our white paper below that...