Drug approval prediction based on the discrepancy in gene perturbation effects between cells and humans.

ABSTRACT:

Background

Poor translation between in vitro and clinical studies due to the cells/humans discrepancy in drug target perturbation effects leads to safety failures in clinical trials, thus increasing drug development costs and reducing patients' life quality. Therefore, developing a predictive model for drug approval considering the cells/humans discrepancy is needed to reduce drug attrition rates in clinical trials.

Methods

Our machine learning framework predicts drug approval in clinical trials based on the cells/humans discrepancy in drug target perturbation effects. To evaluate the discrepancy to predict drug approval (1404 approved and 1070 unapproved drugs), we analysed CRISPR-Cas9 knockout and loss-of-function mutation rate-based gene perturbation effects on cells and

SUBMITTER: Park M 

PROVIDER: S-EPMC10366401 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature