Creating tools to identify optimal treatments for rheumatoid arthritis and breast cancer are focuses of the 2019 Gerstner Family Career Development Awards.
This year's awardees are Elena Myasoedova, M.D., Ph.D., a rheumatologist at Mayo Clinic's Minnesota campus and Bhavika Patel, M.D., a radiologist at Mayo's Arizona campus. Both researchers seek to apply data centric approaches to medical care, sparing patients unnecessary complications and providing enhanced disease treatment.
For Dr. Myasoedova, rheumatology care is a family tradition. "My grandfather and mom were both professors of rheumatology," she says. "This is how I became interested in improving outcomes for rheumatoid arthritis treatment."
Rheumatoid arthritis is a chronic autoimmune disorder that causes irreversible joint and organ damage. Early, effective treatment is needed to avoid severe disability and even death. The most commonly used rheumatoid arthritis medication, methotrexate, is ineffective in 30% to 40% of patients. Methotrexate also must be taken for three to six months before doctors can determine if it's working, and — if it isn't — try something else, which imposes a costly delay for patients.
"The window of opportunity for early treatment is about three months," Dr. Myasoedova says. "Without timely and effective intervention, we lose a lot of momentum in attacking the disease."
Using artificial intelligence, Dr. Myasoedova is building an algorithm that can predict an individual's response to methotrexate. The algorithm incorporates genomic, clinical, sociodemographic and blood test data from people with early rheumatic arthritis who have been treated with methotrexate.
"Analyzing and synthesizing all this information into a model is beyond the capabilities of a regular statistical model," Dr. Myasoedova says. "Artificial intelligence is able to streamline that process and create a model to predict the likelihood of therapeutic response."
This work, undertaken in conjunction with the Center for Individualized Medicine Pharmacogenomics Program, is a pilot project that can potentially provide a foundation for studies of emerging rheumatoid arthritis treatments, including biologics and small molecule therapies.
"Eventually, I hope we will be able to create an artificial intelligence platform where, based on the patient's bloodwork, we can match that patient's characteristics to the medication that would be most beneficial," Dr. Myasoedova says.
Treatment for early stage or locally advanced breast cancer generally involves chemotherapy or other medical treatment, followed by surgery and additional medical therapy. Currently there is no precise way to determine whether each additional treatment benefits an individual patient.
For some patients, presurgical treatment kills all cancer at the tumor site — so it's unclear what benefit the surgery provides. After surgery, however, patients whose tissue tests cancer-free might have residual tumor DNA in their bodies and may benefit from additional treatment.
"Patients with breast cancer are often overtreated and sometimes under-treated, due to the lack of biomarkers that could help personalize treatment plans," Dr. Patel says. "In recent years, overall survival for breast cancer has improved tremendously. But we need biomarkers to accurately identify patients with residual disease after surgery while sparing others who can safely skip postoperative treatment."
Dr. Patel's research team is utilizing two such biomarkers. The first is a blood test to detect residual tumor DNA circulating in patients' blood after breast cancer treatment. This state-of-the- art blood test — developed in collaboration with the University of Cambridge and TGen, a translational genomics research institute in Phoenix — was recently described in Science Translational Medicine. The second utilizes quantitative image analysis tools to identify patterns and metrics detectable on breast cancer patients' contrast-enhanced imaging studies before, during and after treatment.
"Combined with imaging and clinical assessments, measurements of circulating tumor DNA can help guide treatment strategies in individual breast cancer patients, with the use of a fusion biomarker. We can potentially change the paradigm for breast cancer treatment," Dr. Patel says. "Ultimately, the goal is that these biomarkers can inform personalized therapies, to improve breast cancer patients' quality of life and avoid unnecessary treatments."
Funding for the Gerstner Family Career Development Awards in the Center for Individualized Medicine is provided by The Louis V. Gerstner, Jr. Fund at Vanguard Charitable.
The awards are given each year to early-stage investigators to advance individualized therapies. Another goal is to promote a specialized workforce capable of moving individualized medicine from discovery into patient care.
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Tags: #Artificial Intelligence, #personalized therapies, biomarkers, breast cancer, Cancer, center for individualized medicine, circulating tumor DNA, Dr. Bhavika Patel, Dr. Elena Myasoedova, Genetics, genomics, Gerstner Family Career Development Awards, mayo clinic, medical research, methotrexate, Precision Medicine, Research, Rheumatoid Arthritis, TGen, University of Cambridge