Artera shared on Friday that it will present two studies at the American Society of Clinical Oncology (ASCO) meeting featuring the use of its multimodal artificial intelligence (MMAI) model to stratify patients with prostate cancer who will benefit from added treatment and to predict prostate cancer outcomes after prostatectomy."These studies reinforce our commitment to the rigorous clinical validation of the ArteraAI Prostate Test and our broader MMAI platform," said Timothy Showalter, Chief Medical Officer of Artera. "Together, they reflect our mission to empower clinicians and patients with personalised, actionable insights that support confident, shared decision-making in prostate cancer care."Identifying candidates for added therapyThe first study, conducted as part of the STAMPEDE trial, used the ArteraAI Prostate Test to identify patients with high-risk non-metastatic prostate cancer who would benefit most from adding androgen receptor pathway inhibitor (ARPI) abiraterone acetate and prednisolone with or without another ARPI, enzalutamide, to standard of care (SOC) androgen deprivation therapy. While the STAMPEDE trial helped cement ARPIs as the SOC for high-risk patients, treatment responses have varied, and associated adverse events highlight the need for prognostic and predictive biomarkers. When evaluated in 555 patients treated with SOC plus ARPIs and 781 treated with SOC alone, researchers from University College London Cancer Institute found that higher continuous MMAI scores were linked to worse outcomes over a median follow-up of six years. Among the cohort, 25% of men tested positive for a biomarker that signalled they would benefit from treatment with ARPIs; those who tested positive for the biomarker and received ARPI had a 9% risk of prostate cancer-specific mortality over five years compared with a 17% risk for those who received SOC. In contrast, patients without the biomarker did not benefit much from ARPI; those who received ARPI had a 4% mortality risk over five years compared with a 7% risk for those who did not receive it. "While traditional tests flag patients at risk of poor outcomes, they don't personalise treatment decisions," said study author Nick James. "Our collaboration with Artera allows us to uncover patterns invisible to the human eye and optimise treatments like never before. The AI tool allows us to connect beneficial treatments to the patient, while sparing those who may suffer unnecessary side effects, or even premature death, if they receive ARPIs they don't need."Prostatectomy predictionsIn the second study, researchers from the University of California, San Francisco validated a digital pathology-based MMAI model for predicting radical prostatectomy outcomes in patients with and without biochemical recurrence. The procedure is highly effective in localised prostate cancer; however, the researchers reported that 20% to 40% of men who undergo prostatectomy still experience biochemical recurrence within 10 years. Despite this statistic, tools to predict risk and inform treatment choices in this population are still lacking. Analysis of 640 cases with MMAI scores with images and clinical data revealed that after adjusting for post-radical prostatectomy Cancer of the Prostate Risk Assessment (CAPRA-S) score, MMAI scores remained independently associated with any metastasis (hazard ratio [HR] = 1.76) and bone metastasis (HR = 2.72). It was also significantly associated with disease progression in a subset of 561 patients with undetectable prostate-specific antigen following surgery (HR = 1.51). Using a previously established cutoff from patients with biochemical recurrence, those classified as high-risk via MMAI after prostatectomy had a significantly higher 10-year risk of any metastasis (18%) and bone metastasis (16%) compared with low-risk patients (3% and 1%, respectively)."This study validates the radical prostatectomy MMAI model, originally developed in patients with biochemical recurrence, as an independent prognostic tool in both biochemical recurrence and general post-radical prostatectomy settings, even when controlling for a validated clinical risk model," the authors wrote. The findings show that the model could help guide personalised treatment following radical prostatectomy "while offering advantages in accessibility, efficiency and cost compared to existing platforms."