Computing Rx: Dr. Li Chen Fuses Pharmacy and Technology

Cr. Chen poses in front of computers in the lab Dr. Li Chen

January 28, 2019

By Matt Crouch

AUBURN, Alabama – For someone with a background in biology, if you were to ask them to pair another science with it you could expect options like chemistry, zoology or maybe pharmacology. What you would not expect is computer science. For Harrison School of Pharmacy faculty member Dr. Li Chen, it was a logical combination.

Chen arrived on The Plains in August, 2017, joining the Department of Health Outcomes Research and Policy as part of Auburn University’s omics and informatics strategic cluster hire initiative. One of the strongest and fastest-growing areas within modern biology, those in omics and informatics investigate different aspects of the biology of a huge range of species while employing a common thread of omics based approaches and informatics for the analysis of the data sets produced.

“I studied biostatistics, which is the analyzing of large-scale biomedical data for biomedical research,” said Chen. “When analyzing big data, I realize I need some computer skills for handling such large-scale data, which was otherwise impossible.”

Chen’s expertise in these areas was recognized recently with a New Investigator Award from the American Association of Colleges of Pharmacy (AACP) for his project titled, "Machine Learning Methods to Evaluate Safety and Efficacy of FDA-Approved Orphan Drugs." The New Investigator Award provides start-up funding for the independent research programs of early-career pharmacy faculty. This grant is intended to be the first extramural research funding received by a faculty member as a principal investigator (PI), with the goal that research funded by the NIA will provide a foundation for future scholarly endeavors and continued extramural funding success.

Dr. Chen’s proposed study, under the mentorship of Drs. Salisa Westrick and Jingjing Qian, centers around safety and efficacy of orphan drug treatments among Medicaid beneficiaries diagnosed with corresponding orphan diseases.

The Orphan Drug Act, introduced in 1983, encourages pharmaceutical companies to develop orphan drugs for rare diseases, the cost of which are very high. Approximately 15 million patients with rare diseases are children, making Medicaid, the largest single insurer of children in the United States, a valuable source when evaluating the orphan drugs.

His study will use two years (2011-12) of Medicaid claim data in 11 states to assess clinical safety and efficacy of orphan drug treatments among Medicaid beneficiaries diagnosed with corresponding orphan diseases.

Relying on his background in biostatistics and informatics, Chen will assess clinical safety and efficacy of orphan drugs based on the patients in Medicaid claim data.

“The comparative analyses between treated and untreated patients diagnosed with same orphan indication, and among patients using different orphan drugs with the same rare indication will investigate possible cost-effective treatment, which may help decrease the medical cost,” said Chen. “At the conclusion of the study, we will not only develop machine learning model that predicts clinical efficacy and safety for orphan drug users in the real-world population, but also offer a suggestion of best treatment option among multiple treatments for the same rare indication.”

After receiving a bioinformatics degree at Harbin Medical University in China, Chen made his way to the United States to pursue his graduate education at Johns Hopkins University in Baltimore, Maryland. He completed a master’s in biostatistics along with a second master’s in computer science. Looking for a place to fine-tune his work, he was drawn to Emory University and its medical school as a place to complete his Ph.D. in computer science and informatics.

Chen’s biggest strength to the school is applying his biology base knowledge to data analysis and developing new ways to utilize it in treating diseases.

“Right now, there is so much data produced by biological labs and you need to find the association between biologic data and treatments,” said Chen. “Having the data analysis and data sets, that is very important. We also need to develop software, web server, and come up with new ways to find the information you want. I think this is a very important application of biological science research.”

In the past, Chen has developed several software applications, including a web server and database for large-scale genomics computing, statistical computing programs to compare various data sets and genomic intervals, and a software predictive model of microbiome data.

“Once you have the data and larger scale data, I am like the bridge between the two areas,” said Chen. “We can take applied statistics from lab experiments and find out which drugs may be most effective in treating a disease.”

The potential for collaboration is something that interested Chen about his current position. As part of the cluster hire, he regularly collaborates with others in his cluster from the College of Agriculture, College of Science and Mathematics, College of Veterinary Medicine and Samuel Ginn College of Engineering. As part of his position, Chen has also taken on the role of adjunct assistant professor within the Gin College of Engineering Department of Computer Science and Software Engineering.

“What attracted me most was the omics cluster hire because in the cluster, you can collaborate with people with similar interests and expertise,” said Chen. “Not only work in pharmacy, but also have connection with people outside of the school.”

Chen is already working on a project dealing with genetic variance in humans, using tools to identify drugs that target those variances and develop new treatments. He is also working on a metagenomics project that looks at the bacteria within the human body to determine how it can be used in treating certain conditions.

Within HSOP, Chen is working with Dr. Amit Mitra, another cluster hire, on analyzing drug data to target existing drugs that could be used as a secondary cancer treatment when the patient builds a resistance to the primary drug.

“We are all working toward a similar goal, which is to interpret the human genome and find some cure that can help us prevent further disease,” said Chen. “Working together, we can continue to improve human health and find better treatment for diseases.”

----------

About the Harrison School of Pharmacy

Auburn University’s Harrison School of Pharmacy is ranked among the top 20 percent of all pharmacy schools in the United States, according to U.S. News & World Report. Fully accredited by the Accreditation Council for Pharmacy Education (ACPE), the School offers doctoral degrees in pharmacy (Pharm.D.) and pharmaceutical sciences (Ph.D.) while also offering a master’s in pharmaceutical sciences. The School’s commitment to world-class scholarship and interdisciplinary research speaks to Auburn’s overarching Carnegie R1 designation that places Auburn among the top 100 doctoral research universities in the nation. For more information about the School, please call 334.844.8348 or visit http://pharmacy.auburn.edu.

Making Medications Work Through Innovative Research, Education and Patient Care

Last Updated: January 28, 2019