AI-powered omics-based drug pair discovery for pyroptosis therapy targeting triple-negative breast cancer.

ABSTRACT: Due to low success rates and long cycles of traditional drug development, the clinical tendency is to apply omics techniques to reveal patient-level disease characteristics and individualized responses to treatment. However, the heterogeneous form of data and uneven distribution of targets make drug discovery and precision medicine a non-trivial task. This study takes pyroptosis therapy for triple-negative breast cancer (TNBC) as a paradigm and uses data mining of a large TNBC cohort and drug databases to establish a biofactor-regulated neural network for rapidly screening and optimizing compound pyroptosis drug pairs. Subsequently, biomimetic nanococrystals are prepared using the preferred combination of mitoxantrone and gambogic acid for rational drug delivery. The unique mechanism of ob

SUBMITTER: Ouyang B 

PROVIDER: S-EPMC11364624 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature