Chemistry and Chemical Biology ETDs

Publication Date

Spring 3-26-2025

Abstract

DRUG TARGETS ILLUMINATION: AN EVIDENCE-BASED DATA ANALYTICS & INFORMATICS APPROACH TO HYPOTHESIS GENERATION THROUGH CLINICAL TRIALS AND GENOMIC VARIANTS

Target Illumination Clinical Trial Analytics with Cheminformatics (TICTAC) introduces a scalable data integration pipeline that aggregates multivariate clinical trial evidence to systematically rank disease–target associations. By harmonizing metadata from AACT and employing confidence-scoring techniques, TICTAC facilitates hypothesis-driven target selection for drug discovery, enabling a data-driven approach to therapeutic development. In parallel, a bioinformatics-driven analysis of gnomAD exome mutations in the ZPR1 gene highlights the broader role of genetic variants in disease association. By employing variant effect predictors, protein stability modeling, and ACMG/AMP guidelines, this study identifies high-impact ZPR1 mutations and reveals significant ethnic disparities in their prevalence. These findings emphasize that genetic variants contribute to disease mechanisms beyond traditional biological targets and merit further exploration in drug discovery workflows. While these two approaches operate independently, they collectively reinforce the need for a multifaceted strategy in drug discovery and development. Researchers can enhance disease modeling, refine biomarker discovery, and optimize therapeutic target selection by integrating insights from clinical trial analytics and genomic variant interpretation. Future efforts should explore deeper incorporation of genetic insights into cheminformatics-driven analytics to advance targeted therapeutic interventions and improve precision medicine strategies.

Project Sponsors

Partially supported by US National Institutes of Health ‘Illuminating the Druggable Genome Knowledge Management Center’ (IDG KMC), National Institutes of Health (NIH) Common Fund, UNM Comprehensive Cancer Center Support Grant – Provided by the National Cancer Institute (NCI) Institutional Development Award (IDeA) – Funded by the National Institute of General Medical Sciences (NIGMS) of the NIH

Language

English

Keywords

Drugs, Disease-Target associations, Clinical Trial, Analytics, Cheminformatics, Bioinformatics, ZPR1

Document Type

Dissertation

Degree Name

Chemistry

Level of Degree

Doctoral

Department Name

Department of Chemistry and Chemical Biology

First Committee Member (Chair)

Dr. Jeremy Edward

Second Committee Member

Dr. Jeremy Yang

Third Committee Member

Dr. William Garver

Fourth Committee Member

Dr. Yi He

Comments

For further details, visit the official GitHub repository: https://github.com/unmtransinfo/TICTAC

All files are accessible for download at: https://unmtid-dbs.net/download/TICTAC/

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