Preclinical Development – Chemical
2019 PharmSci 360
Advances in artificial intelligence (AI) are gaining ground for their applicability in drug development. In silico drug repurposing approaches have been showing great promise to provide safer, quicker, and cheaper solution for drug development. However, how to utilize implement advanced AI approaches into computational drug repositioning framework for augmenting successful rate of disease therapies is still an open question. In this presentation, we will elaborate on and exemplify a few deep learning-based drug repurposing strategies including (1) Deciphering immune and mitochondria continuum with augmented representation learning; (2) An autoencoder-based patient stratification for advancing precision medicine-based drug repositioning; (3) A deep learning-based sentiment analysis for drug indication extraction. The presentation will be ended with key lessons learned from real-word applications of deep learnings.