Drug Response Prediction Provides a Biologically Relevant Benchmark for Perturbation Response Models
Brouwer, N.; Damyanov, M.; Argelo, J.; Vis, D. J.; Reinders, M.; Wessels, L.
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Perturbation response models (PRMs) predict transcriptional responses to interventions such as gene knockout or drug treatments. While simple baseline models match PRMs in reconstructing post-treatment profiles, we show that drug response predictors trained on PRM-generated profiles significantly outperform those trained on baseline or pre-treatment profiles. Unlike simple baseline models, PRMs preserve variation in response-relevant genes, making them a highly valuable tool for predicting drug response.
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