Patrick Wu

Graduate Trainee, Vanderbilt University

2 active projects

Duplicate of Drug Repurposing Validation Study (for dataset v5)

New drug development is expensive, takes a long time, and often fails. An alternative approach to finding effective drugs for diseases is to find new indications for existing drugs, a method known as drug repurposing. Since existing drugs have well-characterized…

Scientific Questions Being Studied

New drug development is expensive, takes a long time, and often fails. An alternative approach to finding effective drugs for diseases is to find new indications for existing drugs, a method known as drug repurposing. Since existing drugs have well-characterized safety profiles, drug repurposing can potentially reduce the risk of failure caused by adverse reactions and save costs associated with studies aimed at gathering safety data. However, a known technical barrier to successfully repurposing drugs is the identification of good drug candidates. Clinical data stored in electronic health records (EHR) offer an opportunity to systematically identify drug repurposing candidates.

Project Purpose(s)

  • Drug Development
  • Methods Development

Scientific Approaches

We plan to use the All of Us dataset to validate an approach to identify drug repurposing candidates. We will look at the effect of drug repurposing candidates on lab biomarkers, using a self-controlled case series study design. To identify patient cohorts, we will use SQL code designed to extract data from EHR data organized using the OMOP/OHDSI Common Data Model. We will then use an R package that we have developed to process the extracted EHR data and conduct statistical analyses.

Anticipated Findings

We hope to validate the drug repurposing candidates that we have identified in our local EHR database, and to demonstrate the portability of our pipeline in the All of Us dataset. The main contribution of this study would be a generalizable approach to mine clinical data in EHRs to identify promising drug repurposing candidates, drugs that future experiments can be designed to verify.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Patrick Wu - Graduate Trainee, Vanderbilt University

Drug Repurposing Validation Study

New drug development is expensive, takes a long time, and often fails. An alternative approach to finding effective drugs for diseases is to find new indications for existing drugs, a method known as drug repurposing. Since existing drugs have well-characterized…

Scientific Questions Being Studied

New drug development is expensive, takes a long time, and often fails. An alternative approach to finding effective drugs for diseases is to find new indications for existing drugs, a method known as drug repurposing. Since existing drugs have well-characterized safety profiles, drug repurposing can potentially reduce the risk of failure caused by adverse reactions and save costs associated with studies aimed at gathering safety data. However, a known technical barrier to successfully repurposing drugs is the identification of good drug candidates. Clinical data stored in electronic health records (EHR) offer an opportunity to systematically identify drug repurposing candidates.

Project Purpose(s)

  • Drug Development
  • Methods Development

Scientific Approaches

We plan to use the All of Us dataset to validate an approach to identify drug repurposing candidates. We will look at the effect of drug repurposing candidates on lab biomarkers, using a self-controlled case series study design. To identify patient cohorts, we will use SQL code designed to extract data from EHR data organized using the OMOP/OHDSI Common Data Model. We will then use an R package that we have developed to process the extracted EHR data and conduct statistical analyses.

Anticipated Findings

We hope to validate the drug repurposing candidates that we have identified in our local EHR database, and to demonstrate the portability of our pipeline in the All of Us dataset. The main contribution of this study would be a generalizable approach to mine clinical data in EHRs to identify promising drug repurposing candidates, drugs that future experiments can be designed to verify.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Patrick Wu - Graduate Trainee, Vanderbilt University

Collaborators:

  • Kyle Webb - Project Personnel, NIH
  • Josh Denny - Other, All of Us Program Operational Use
  • David Schlueter - Research Fellow, NIH
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