Application of Informatics Tools to Facilitate the Practice of Precision Medicine with Genomic Testing and Clinical Data

<p>The practice of precision medicine considers a variety of sources of information to optimize patient care. Factors such as patient demographics, clinical history, and lab test values have well understood effects on treatment outcomes and influence decision making. However, effective inclusion of biomolecular data such as protein expression and DNA sequencing data within the practice of precision medicine needs continued study. Informatics tools offer solutions to allow these complex data sources to be effectively embraced. Utilization of informatics tools to visualize data pertaining to the gene selection practices of pharmacogenomic (PGx) tests effectively communicated large amounts of information into concise heatmaps. After a thorough search identifying potential PGx tests, their detection rates were assessed based on their gene targets and the genomic frequencies of various ethnic groups. Detection rates were defined as the proportion of a prospective ethnic population where PGx tests selected both variants within genotypes of requiring alterations in medication therapy. Detection rates had high levels of variance between different assays and ethnic groups. Our results strongly support the practice of clinicians considering a patient’s ethnic background when selecting a PGx test that is right for them to ensure effective testing. In addition to genetic test selection, applied informatics tools allow for better utilization of biomolecular information in patient prognosis assessment and therapy selection. We demonstrated this on a cohort on non-small cell lung cancer patients receiving immune checkpoint inhibitor (ICI) therapy. Through multivariate statistical models and vi survival analyses, we demonstrated the impact of various clinical and biomolecular variables on patient survival. Our results showed patients experiencing immune related adverse events (irAEs) and their timing had a significant impact on patient survival time. Additionally, we demonstrated the timing of genotype targeted tyrosine kinase inhibitor therapy relative to ICI therapy has a significant impact on patient survival time as well. Variables with less understood associations with patient survival were effectively contextualized with common clinical variables within multivariate modeling approaches. Continued implementation of informatics approaches is vital to effectively embrace a precision medicine approach in patient care.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Pharmaceutical Sciences

Year dc:date.available

2023

Author dc:creator

• Sayer, Michael

Contributors dc:contributor

• Moom Roosan, Ph.D, Chair
• Rennolds Ostrom, Ph.D.
• Ajay Sharma, Ph.D.
• Sun Yang, Ph.D.

• Bioinformatics
• Pharmacogenomics
• Non-Small Cell Lung Cancer
• Precision Medicine
• Clinical Epidemiology
• Oncology
• Other Pharmacy and Pharmaceutical Sciences
• Translational Medical Research

Repository record dc:identifier

https://digitalcommons.chapman.edu/pharmaceutical_sciences_dissertations/24

OAI identifier oai:identifier

oai:digitalcommons.chapman.edu:pharmaceutical_sciences_dissertations-1025