FDA grants De Novo authorization for first AI-powered prostate cancer prognostic tool

AI-powered prostate cancer tool authorized: ©Drmicrobe - stock.adobe.com

The U.S. Food and Drug Administration has granted De Novo authorization to ArteraAI Prostate, making it the first and only AI-powered software authorized to prognosticate long-term outcomes for patients with non-metastatic prostate cancer.

The decision establishes ArteraAI Prostate as a regulated Software as a Medical Device and creates a new product code category for future AI-powered digital pathology risk-stratification tools. The technology can now be implemented at the point of diagnosis in qualified pathology labs across the U.S., addressing a critical gap in prostate cancer care by delivering actionable insights without delays.

“This is a defining moment for AI in cancer care,” said Andre Esteva, CEO and co-founder of Artera. “The FDA's decision validates the power of our MMAI platform to deliver on our vision to create AI-guided tools that enable data-backed and tailored treatments for each patient, leading to more confidence throughout the cancer journey, and ultimately, save more lives.”

Adam Cole, founder and chief science officer at TruCore Pathology Group, said the authorization underscores the growing excitement over AI’s role in clinical workflows. “We need to utilize deep learning AI models to augment and better refine what a pathologist is able to report and Artera is leading the charge,” he said. “As the demand for pathology services continues to outpace available capacity, tools like ArteraAI Prostate are critical. Implementing this software enhances our ability to deliver personalized insights more quickly, improves workflow efficiency, and allows us to scale services while increasing the quality of care.”

The De Novo authorization — a process reserved for novel medical innovations — also includes a Predetermined Change Control Plan, allowing Artera to validate compatibility with additional digital pathology scanners without further 510(k) submissions. This milestone follows ArteraAI Prostate’s earlier Breakthrough Device Designation and builds on the company’s broader pipeline of multimodal AI-powered cancer care software.

AI advancements reshape cancer diagnostics and prognostics

In recent years, artificial intelligence has moved from theoretical promise to clinical reality in oncology, particularly in diagnostics and prognostics. Advances in deep learning, digital pathology, and multimodal data integration are enabling tools that can analyze complex patient information — such as histopathology slides, clinical records, imaging, and genomic data — to predict disease progression and guide treatment strategies.

One of the most significant developments has been the shift toward AI models that provide prognostic insights at the point of diagnosis. These systems can help identify which patients are more likely to experience aggressive disease, reducing uncertainty for clinicians and patients alike. By integrating seamlessly into pathology workflows, AI-enabled software can return results in hours rather than days or weeks, helping to avoid treatment delays.

Digital pathology itself has benefited from increased scanner adoption and standardization, making it easier to train and validate AI algorithms. In parallel, regulatory bodies have begun to establish clearer pathways — such as the FDA’s De Novo process — for bringing these tools to market as medical devices, rather than limiting them to laboratory-developed tests.

Another important advance is the incorporation of change control plans within regulatory approvals. This approach allows developers to update AI software — for example, to support additional scanners or adapt to new data sources — without restarting lengthy approval processes. This flexibility is particularly valuable in AI, where rapid iteration is key to maintaining performance across diverse clinical settings.

As adoption grows, experts point to the dual benefits of AI in cancer care: improving diagnostic accuracy and efficiency for overburdened pathology departments, and enabling more personalized treatment planning based on a patient’s unique risk profile. The result is a health care environment where AI acts as an extension of the clinician’s expertise, potentially improving outcomes while optimizing limited resources.