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Personalized therapy requires precision AI

The integration of AI technology in cancer care can improve accuracy and aid in clinical decision-making using prostate cancer biomarkers.

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Solving challenges across the cancer care industry

There are a number of key opportunities within the cancer treatment space. At Artera, we approach them in a way that benefits both clinicians and patients.

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Opportunity: Uncertainty reduces confidence in treatment decisions

Not knowing whether a patient will benefit from a certain therapy can make it difficult for clinicians and patients to feel confident that they are choosing the optimal course of treatment. This can lead to poor patient adherence and added stress on the patient and clinician.

Our Approach

With predictive and prognostic data, clinicians feel informed and confident with their treatment decisions. Patients and clinicians can review the information provided by the test together to determine the optimal treatment path forward. The results are available to review within 2-3 days after receipt of the patient's specimen.

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Opportunity: Diversity in data is critical for generalizability

Many clinical trials do not represent minority populations, which can result in treatments that are less effective for these groups. In the U.S., prostate cancer disproportionately impacts African American men, and yet this group is historically underrepresented in clinical trials.The State of Cancer Health Disparities in 2022 | AACR. (2022, June 29). Cancer Progress Report.

Our Approach

Artera's MMAI models were intentionally developed using cohorts that consisted of about 20% African Americans, which is reflective of the 16% prevalence of prostate cancer in this patient population. Our models have demonstrated similar performance in African Americans and non-African Americans.

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Opportunity: Solving the problem of finite tissue

There is a finite amount of available tissue from a biopsy, underscoring the need for tissue preservation.

Our Approach

The ArteraAI Prostate Test does not consume tissue. We use a patient's existing pathology slides and digitize them for the AI model.

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Opportunity: Empowering physicians and patients through AI

AI has the potential to transform healthcare delivery and has already taken flight across a number of therapeutic areas. This rapid adoption can create concern among clinicians that the technology is going to "replace" them.

Our Approach

The ArteraAI Prostate Test is intended to augment the clinician's work by providing a tool that can personalize therapy and optimize treatment decision-making between clinicians and patients.

Artera predicts therapeutic benefit for patients

Using a large volume and a wide variety of clinical data and digital pathology images, our AI-enabled test accomplishes things that conventional techniques and computers cannot do alone.

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Shaping the future of cancer treatment decisions


Artera’s unique MMAI architecture can be used to create biomarkers that have the potential to guide personalized treatment decision-making for patients across a variety of cancer types. The growing adoption of digital histopathology will eventually support the global distribution of AI biomarker tests in the future, enabling broad access to therapy personalization.

Conferences and publications featuring Artera

Case Western Reserve University

Daniel Spratt, MD

Dr. Spratt discusses the validation of an MMAI prognostic biomarker and how the model further stratifies risk in men with high-risk disease, a population for which there are numerous treatment decisions.

Northwestern University

Ashley Evan Ross, MD, PHD

Dr. Ross discusses external validation of an MMAI prognostic model in patients with high- and very high-risk disease. Additionally, the model was shown to further stratify risk within this group, enabling more personalized treatment for these patients.

University of California at San Francisco

Felix Feng, MD

Dr. Feng discusses the development and validation of pathology-based deep learning predictive and prognostic tools to personalize treatment decisions for patients with localized prostate cancer. UroToday Article


Jonathan D. Tward, MD, PHD, FASTRO

Dr. Tward discusses how an MMAI prognostic risk stratification model can further risk-stratify within a given NCCN risk group, providing insights to better inform treatment decisions for patients with localized prostate cancer. UroToday Video UroToday Article


Dr. Roach discusses how the performance of the multimodal artificial intelligence (MMAI)-derived prognostic biomarker is comparable between African American and non-African American subgroups. ASCO Abstract

Osama Mohamad, MD

Dr. Mohamad discusses the development and validation of multimodal AI-based predictive and prognostic biomarkers for localized prostate cancer. UroToday Article

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