*This event was postponed due to COVID-19.
Presentation Detail
- Speaker: Sungwon Lim, PhD, CEO & Co-Founder of ImpriMed, Inc.
- Date: March 19, 2020
Research Abstract
Introduction
For a life-threatening disease like cancer, optimal treatment may need to be personalized for each patient. We developed a functional precision medicine platform based on a novel chemosensitivity assay to identify effective drugs most likely to benefit an individual canine lymphoma patient, ultimately enabling veterinary oncologists to treat lymphoma with an individualized regimen. This study evaluated the correlation between our ex vivo data-driven prediction and reported responses in a series of canine lymphoma patients.
Methods
We performed our ex vivo drug sensitivity assay on live cancer cells from fresh fine needle aspirates taken from affected lymph nodes of canine lymphoma patients. The drug panel included the seven most common chemotherapy drugs for canine lymphoma treatment: doxorubicin, cyclophosphamide, vincristine, prednisone, lomustine, TANOVEA-CA1, and L-asparaginase. 180 correlations between drug response prediction and clinical outcome were evaluated retrospectively in 80 canine lymphoma patients provided by 14 clinical sites, by collecting the patient’ s treatment history and the post-treatment clinical outcomes 60-90 days after our prediction report.ResultsEach of the 80 lymphoma patients showed a unique drug response profile from the ex vivo chemosensitivity test. The positive predictive value of the test was 82.4% and the negative predictive value was 80.2% with 74.4% sensitivity and 86.7% specificity.
Conclusion
This study proved the need for individualizing chemotherapy for canine lymphoma patients by revealing unique drug response profile of each patient. The drug sensitivity test developed in this study showed high positive and negative predictive values ex vivo.
Clinical significance of the results
The ex vivo drug sensitivity test developed in this study may help improving treatment outcomes in individual canine lymphoma patients by providing predictive information on chemotherapy sensitivity.
