Curiosity Drives Career Change

Pharm.D. Alumna Returns for Ph.D. Education to Combat Life-threatening Bacterial Infection, Antibiotic Resistance 

Sometimes life pulls you not in a different direction, but in a deeper direction, to more fully experience and explore your current passion. This was the case with University of Houston College of Pharmacy (UHCOP) alum ThanhPhuong Le, Pharm.D. ('18). Working as a pharmacist for three years at a gastroenterology specialty pharmacy, she enjoyed her career – but she had a spark to dig deeper.

"Being a pharmacist gave me the privilege to explore a variety of pharmacy related subjects to enhance patient care decisions," Le said. "A career in pharmacy demands the pharmacist to constantly keep up with therapeutic projects to ensure patients receive the correct, most cost-effective treatments. However, the more deeply I dove into any specific subject, the more I realized that what I understood about the topic was just scratching the surface."

Growing Threat from C. diff

As her spark for expanded knowledge was growing, Le was noticing a trend at her practice: relatively high recurrence rates of the gut microbiome disease, Clostridioides difficile (C. diff) infection (CDI) — the most common health care-associated infection in the U.S., with approximately 500,000 cases per year, according to Centers for Disease Control and Prevention.

"I was initially interested in CDI because of its limited treatment options," Le said. "It is hard to treat, and clinical guidelines only recommend one antibiotic, fidaxomicin (FDX), as first-line therapy for most cases. The corresponding increase in FDX use has placed a tremendous selection pressure for the development of FDX resistance."

Backyard Expertise

Ready to accelerate her research endeavors, Le sought out opportunities to gain translational research experience. A natural choice for her was to contact nationally recognized C. diff expert and UHCoP Robert L. Boblitt Endowed Professor Kevin W. Garey, Pharm.D., M.S., FASHP, FIDSA, FCCP, who precepted Le in an infectious diseases rotation during her final year of pharmacy school. Much to her excitement, Le was welcomed back to Garey's lab where she volunteered in her spare time while still working full-time as a clinical pharmacist.

"Being a novice in the lab encouraged me to work harder, to ask more questions, and to do more research on the topics of the current project," Le said. "I became fascinated by the knowledge a person must possess to become a research specialist blending therapeutic knowledge with research methods. I realized how much I would like to be a part of this exciting journey."

Inspired by the experience of being back in the lab and part of Garey’s motivated and productive laboratory team, Le decided to go all in on pursuing a career in research through the Ph.D. program concentration in pharmacology at UHCOP.

"When I decided to go back to school, many people asked me, 'Aren’t you burned out yet?’ But working for the last three years let me know that I was already on the right path; now I am just taking it to a higher level," Le explained. "This degree track blends well with my background in pharmacy and my long-term career goals, which are to pursue a career in academia where I can utilize my expertise both as a pharmacist and Ph.D. to further knowledge and train the next generation of researchers."

Federal Support

Le was recently awarded a one-year, $76,727 postdoctoral Biomedical Informatics and Data Science fellowship from National Library of Medicine (NLM) for her work studying the role of bacterial RNA polymerase in antimicrobial resistance and utilizing machine learning to identify resistance and virulent determinants. In addition to Garey, Le also is working under the mentorship of Rice University Associate Professor Computer Science Todd Treangen, Ph.D.

"I chose biomedical informatics and data analysis as my Ph.D. research because I think the exciting interface between computational and biological sciences can address many challenges in health care and help to advance clinical decision support systems," Le said.

Predicting Resistance

Le will use existing C. diff genomic data and phenotypic assays to identify mutations in the key residues critical to FDX activity and utilize an adapted computational analysis pipeline to predict C. diff behaviors associated with FDX resistance. The computational analysis pipeline will combine sequence analysis with machine learning tools to achieve the goal of predicting phenotype (susceptibility to FDX) from genotype (mutations in C. diff) and address questions of whether genetic changes in key RNA polymerase genes can predict FDX resistance and whether these changes alter the bacteria’s ability to cause disease.

"As antibiotic resistance is rapidly emerging worldwide, I hope to utilize machine learning as a predictive computational tool to identify resistance and virulent determinants, therefore helping to strengthen therapeutic decision-making and improve patient outcomes," Le said.