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A molecular indicator of a specific biological property; a biochemical feature, facet, or pattern that can be used to measure the progress of disease or the effects of treatment. |
Parallel Cascade Identification (PCI) is a mathematical technique that is adept at finding patterns in complex datasets such as those found in biology. PCI has been adapted to predicting outcomes in biological datasets by Dr. Michael Korenberg of Queen's University. Provide us with your data (microarray expression, metabolomics, proteomics, Tissue Micro Arrays, etc.) and we will produce your predictor in a few weeks.
Major Features:
Only a small amount of training data is required. We have instances where only 3 patient's data were used for the training data and the predictor was able to correctly ascertain outcomes in 69% of the cases. For example, when designing a Phase 3 trial based on Phase 2 data there is often 30 or fewer cases to work with. PCI can identify the sub populations that will respond in a Phase 3 trial.
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PCI finds the pattern in the data. Simple biomarkers do not tell the whole story. PCI is a far more reliable way of predicting outcomes.
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PCI is often successful where other techniques are not (e.g. leave one out, neural nets, least squares, clustering, etc.).
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PCI predicts very well symmetrically. That is the predictor can tell you negative and positive outcomes equally well.
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PCI works with a wide variety of data such as microarray expression data, Tissue Micro Arrays (TMAs), proteomics, metabolomics, etc.
It is very cost efficient to discover if PCI will help the design of your clinical trial. If you have the data it is straight forward for us to build a predictor in a few weeks.
Additional Resources:
- Click here for information on an article from Nature that reviews PCI.
- Click here for a paper on predicting outcomes in medulla blastoma.
Click here for a paper on predicting outcomes for myeloid leukemia.
For pricing and further information email or call 866 202 2100 (toll free in Canada) or 403 202 1039 (international).