Machine learning based approaches to predict and overcome treatment resistance in ovarian cancer

Project summary

We will use Artificial Intelligence (AI)/deep learning methods to analyze the rich data bases of genomic, proteomic profiles and histological images of ovarian cancer to achieve the following clinical goals. We will create an accurate predictor of response to first-line platinum-based therapy. Patients not responding to this therapy have an inferior clinical outcome and using our predictor they could be offered alternative therapies at an earlies stage. We will also identify potential therapeutic vulnerabilities of ovarian cancer that are resistant to first-line or maintenance therapy.

This grant was made possible in part by generous donations from Hope for Heather in memory of Heather Weeks; and Judy and Phil Messing in memory of Carol S. Messing.