UCLA

While PathFX is a powerful tool, it has limitations, relying solely on drug-target proteins often fails to fully explain predicted phenotypes and can lead to overprediction due to the complexity of biological networks. To address this, a more nuanced approach is necessary. By investigating each predicted phenotype individually and incorporating external data and literature, researchers can better validate and refine PathFX’s predictions. In this study, we analyze clinical data to identify drugs associated with anemia as a side effect, comparing these drug-phenotype pairs with PathFX's predicted pathways. This comparison will help assess the model’s accuracy in predicting drug-induced side effects. Additionally, a linear regression analysis will quantify the relationship between predicted pathways and observed anemia rates, providing deeper insights into PathFX's predictive strength.