Dr. Yingqi Zhao receives SWOG Coltman Fellowship early-career award

She plans to use the funds to develop new surveillance and diagnostic strategies for immunotherapy trials
Dr. Yingqi Zhao
Dr. Yingqi Zhao Photo by Bo Jungmayer / Fred Hutch News Service

Fred Hutchinson Cancer Research Center biostatistician Dr. Yingqi Zhao has been awarded the Dr. Charles A. Coltman Jr. Fellowship, which recognizes and funds prolific early- and mid-career scientists from affiliated institutions within SWOG, a national clinical trials network.

The Coltman Fellowship, which is sponsored by SWOG’s public charity, The Hope Foundation, includes a two-year, $50,000-a-year grant to support the development of cutting-edge clinical trials within an academic environment.

“I’m really grateful that SWOG and The Hope Foundation are interested in my research,” said Zhao, whose work centers on improving immunotherapy trials and patient outcomes. Unlike chemotherapy, which targets fast-growing cells, immunotherapy encompasses a number of different approaches to harness the patient’s own immune system to destroy the cancer. It is an active area of research across many types of cancers; a growing number of immunotherapies have been approved by the U.S. Food and Drug Administration.

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Since each patient’s immune system is different, treatment that’s extremely effective for one patient could be immensely toxic for another. Different patients may also respond to treatment at different, fairly unpredictable rates.

Using data from previous immunotherapy trials conducted at SWOG-affiliated institutions, Zhao hopes to establish a quantitative model for predicting patient outcomes based on detectable biological factors in each patient. The model will allow clinicians to design a personalized, precision approach to cancer treatment based on both the patient’s biomarkers and the predictive algorithms, hopefully improving both the efficacy and reducing the toxicity of the treatment.

“That’s the strategy,” she said. “It’s personalized, precision medicine for patients so that we can deliver different treatments that account for both efficacy and toxicity.”

The creation and implementation of a personalized statistical method to improve disease management is not a new field of research for Zhao. Before joining the Hutch in 2015, she helped to develop a strategy-based health care delivery model for complex Type 2 diabetes patients at the University of Wisconsin Department of Biostatistics and Medical Informatics.

Current strategies for managing Type 2 diabetes are not always applicable to complex patients, i.e., those over 65 and/or those with other medical conditions. These patients are often excluded from clinical trials due to their additional health concerns. Using electronic health records and claims data, Zhao and her team constructed a model to assess mortality risk and adverse health events in these patients.

Dr. Charles Kooperberg, head of the Fred Hutch Biostatics Program, praised Zhao for her initiative.

“She hit the ground running and is establishing herself as our expert in machine-learning methods for personalized medicine and trial design,” he said.

For Zhao, it’s all connected.

“It’s all related to the field of precision medicine, and using statistical and machine methods to achieve our goals there,” she said.

Read more about Fred Hutch achievements and accolades.

Science writing intern Colin Petersdorf is a junior at the University of Southern California, where he is majoring in biological sciences and minoring in screenwriting. Tweet him @colinpetersdorf to talk medicine, baseball, Star Wars or anything in between.

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