Format

Send to

Choose Destination
Drug Saf. 2020 Feb 28. doi: 10.1007/s40264-020-00915-6. [Epub ahead of print]

Leveraging Human Genetics to Identify Safety Signals Prior to Drug Marketing Approval and Clinical Use.

Author information

1
Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA. rebecca.jerome@vumc.org.
2
Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA.
3
Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
4
Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA.
5
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
6
Center for Technology Transfer and Commercialization, Vanderbilt University, Nashville, TN, USA.

Abstract

INTRODUCTION:

When a new drug or biologic product enters the market, its full spectrum of side effects is not yet fully understood, as use in the real world often uncovers nuances not suggested within the relatively narrow confines of preapproval preclinical and trial work.

OBJECTIVE:

We describe a new, phenome-wide association study (PheWAS)- and evidence-based approach for detection of potential adverse drug effects.

METHODS:

We leveraged our established platform, which integrates human genetic data with associated phenotypes in electronic health records from 29,722 patients of European ancestry, to identify gene-phenotype associations that may represent known safety issues. We examined PheWAS data and the published literature for 16 genes, each of which encodes a protein targeted by at least one drug or biologic product.

RESULTS:

Initial data demonstrated that our novel approach (safety ascertainment using PheWAS [SA-PheWAS]) can replicate published safety information across multiple drug classes, with validated findings for 13 of 16 gene-drug class pairs.

CONCLUSIONS:

By connecting and integrating in vivo and in silico data, SA-PheWAS offers an opportunity to supplement current methods for predicting or confirming safety signals associated with therapeutic agents.

PMID:
32112228
DOI:
10.1007/s40264-020-00915-6

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center