Dr. McKay highlights the ArteraAI Prostate Test

In this interview, Rana R. McKay, MD, discusses use of the ArteraAI test for prostate cancer risk stratification. McKay is a GU medical oncologist and an associate professor of medicine at the University of California, San Diego Health.

Rana R. McKay, MD

Could you provide some background on the growing use of AI in urology and the development of ArteraAI?

The use of AI in uro-oncology has been tremendously expanding and is reshaping our approach to the treatment of patients with urologic malignancies.

Applications for AI are expanding to include new approaches for cancer detection, screening, diagnosis, and also assessment of prognostic and predictive biomarkers to aid in clinical decision making, treatment selection, and drug discovery.

What is the ArteraAI test?

The ArteraAI Prostate Test is both a prognostic and predictive tool for risk stratification of men with localized prostate cancer. It is unique given that in addition to providing prognostic information, it can serve as a marker to predict sensitivity to androgen deprivation therapy (ADT), which is the backbone of systemic therapy for men with prostate cancer. This biomarker aims to identify patients most likely to derive maximum benefit from ADT and spare individuals who are unlikely to benefit from therapy [from] the toxicity of treatment. The test, which simply utilizes digital images from prostate biopsy specimens, outperforms standard clinical tools that are used to inform prognosis for patients.

The Artera AI Prostate Test was developed using a multimodal deep learning architecture that inputs clinical data and distal histopathology from prostate biopsies to improve prognostication and predict sensitivity to ADT for men with prostate cancer. The model was developed and validated using 5 phase 3 trials of over 5000 patients with localized prostate cancer.

What are some of the benefits of ArteraAI for both patients and urologists?

This is a very simple test with many benefits. It mainly utilizes digital images from histopathology slides without wasting tissue for assay performance. It has a rapid test turnaround time, with results [that] can be shared within 5 days after receipt of the patient's specimen, and can provide useful information to guide prognosis and ADT utilization for patients with localized disease.

What are some of the possible implications of widespread adoption of the test?

There is tremendous possibility for widespread adoption given the minimal input requirements for the rest and high yield results. Additionally, this assay was developed and validated utilizing a clinical trial pool including 20% African American men, and the test has excellent performance in diverse patient populations.

Is there anything else that you’d like to add?

It is exciting to think about the application of this model across other genitourinary malignancies, including renal cell carcinoma and urothelial carcinoma. There is the potential to apply this model to inform prognosis and also response to therapy for patients with alternate genitourinary malignancies.