Predicting drug side-effect profiles: a chemical fragment-based approach
2011
Predicting Drug Side-Effects Using Chemical Structures
Sample size: 888
publication
Evidence: high
Author Information
Author(s): Pauwels Edouard, Stoven Véronique, Yamanishi Yoshihiro
Primary Institution: Mines ParisTech
Hypothesis
Can chemical structures of drug candidates be used to predict their potential side-effect profiles?
Conclusion
The proposed method effectively predicts potential side-effects of drug candidates based on their chemical structures.
Supporting Evidence
- The method predicted 1385 side-effects from the chemical structures of 888 approved drugs.
- The study demonstrated high-performance prediction power of the proposed method.
- The method is applicable on large molecular databanks.
Takeaway
This study shows a way to guess what bad effects a medicine might have by looking at its chemical makeup.
Methodology
The study used sparse canonical correlation analysis (SCCA) to correlate chemical substructures with side-effects.
Limitations
Choosing appropriate sparsity parameters and the number of components can be challenging.
Statistical Information
P-Value
almost zero
Digital Object Identifier (DOI)
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