AI Enables Explainable Drug Sensitivity Screenings.

Accelerating anticancer drug discovery is pivotal in improving therapies and patient prognosis in cancer medicine. Over the years, in-silico screening has greatly helped enhance the efficiency of the drug discovery process. Despite the advances in the field, there remains a need for explainable predictive models that can shed light onto the anticancer drug sensitivity problem. A team of scientists at the Computational Systems Biology group within IBM Research has now proposed a novel AI approach to bridge this gap.