A. John Callegari1, Josephine Tsang1, Stanley Park1, Deanna Swartzfager1, Sheena Kapoor1, Kevin Choy2n and Sungwon Lim1*
1ImpriMed Inc., Mountain View, CA, United States,
2Department of Oncology, Blue Pearl Seattle Veterinary Specialist, Kirkland, WA, United States
Dogs with B-cell lymphoma typically respond well to first-line CHOP-based
chemotherapy, but there is no standard of care for relapsed patients. To help
veterinary oncologists select effective drugs for dogs with lymphoid malignancies
such as B-cell lymphoma, we have developed multimodal machine learning
models that integrate data from multiple tumor profiling modalities and predict
the likelihood of a positive clinical response for 10 commonly used chemotherapy
drugs. Here we report on clinical outcomes that occurred after oncologists
received a prediction report generated by our models. Remarkably, we found
that dogs that received drugs predicted to be effective by the models experienced
better clinical outcomes by every metric we analyzed (overall response rate,
complete response rate, duration of complete response, patient survival times)
relative to other dogs in the study and relative to historical controls.
Source : https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2024.1304144/full
