Bayesian tensor factorization for predicting clinical outcomes using integrated human genetics evidence. (arXiv:2207.12538v1 [cs.LG])

The approval success rate of drug candidates is very low with the majority of
failure due to safety and efficacy. Increasingly available high dimensional
information on targets, drug molecules and indications provides an opportunity
for ML methods to integrate multiple data modalities and better predict
clinically promising drug targets. Notably, drug targets with human genetics
evidence are shown to have better odds to succeed. However, a recent tensor
factorization-based approach found that additional information on targets and
indications might not …

arxiv bayesian evidence factorization genetics human lg tensor