Phenotype data - what side effects are caused by a drug - from clinical trials - text mined (1000)
Targets of drugs are also available as a dataset - 500
750 drugs to characterise drugs with similar side effects have similar targets.
- Problem to deal with synonyms in phenotype data - use ontologies (Costart) to cluster the same concepts in the side effects.
- Some side effects are very common - parent terms of more specific side effects in the ontology - these become non-predictive. use a log frequency weight.
- Some side effects are correlated use Gerstein-Sonnhammer-Chothia weights (from HMM).
Use shuffling to normalise the score and get the side effect similarity. Also measure chemical similarity. Low chemical similarity low chance of sharing targets and similar for side effect similarity - need both chemical and side effect similarity for effective description. Side effect much more effective at predicting the same targets than chemical similarity.
Can create a drug-drug network connected when they share a target which will have the same phenotype. Rabeprazole is an exception as it is not a nervous system drug but a stomach drug.
Side effects also occur with the placebo as well as with the drug.
On targets and off targets are treated equally in the model - so they assume the same off target is affected in the case of having the same side effects.