Data-driven drug discovery: investigating the molecular mechanisms of safety and efficacy

NIH RePORTER · NIH · R35 · $13,271 · view on reporter.nih.gov ↗

Abstract

Summary Up to 30% of adverse drug events can be attributed to drug-drug interactions in metabolism or mechanism of action. The study of drug-drug-protein interactions that drive these adverse effects, however, remains an underexplored area of research. This research project aims to offer one of the first comprehensive insights into the effect of genetic variants on adverse drug events, with a particular focus on drug-drug interactions. Through the utilization of large datasets and computational methods, we aim to develop a data-driven approach to identify genetic variations of target protein and metabolizing proteins associated with the development of adverse drug events. Expanding from our current work, we will identify genetic variants affecting the proteins of interest, participants in the study who have experienced the adverse drug events following use of the drugs and conduct association studies to identify any significant variants.

Key facts

NIH application ID
10393864
Project number
3R35GM131905-03S1
Recipient
COLUMBIA UNIVERSITY HEALTH SCIENCES
Principal Investigator
Nicholas P Tatonetti
Activity code
R35
Funding institute
NIH
Fiscal year
2021
Award amount
$13,271
Award type
3
Project period
2019-05-01 → 2024-04-30