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Valar Labs’ CHAI Biomarkers Validated in New Study in European Urology for Predicting Outcomes of High Grade Ta Bladder Cancer

June 13, 2025 --

Valar Labs, a pioneer in AI-powered diagnostics for oncology, announced the publication of its latest research in European Urology, the highest-impact journal in the field of urology. The peer-reviewed study highlights the performance and clinical impact of Valar Labs’ Vesta platform in prognosticating outcomes for patients with high grade Ta non muscle invasive bladder cancer, a population frequently on the borderline of guideline-based risk stratification who may receive different treatment depending on which guideline their provider uses.

Bladder cancer treatment remains highly variable in its outcomes, with limited tools available to tailor therapies to individual patients. Valar Labs’ Vesta platform, built using advanced artificial intelligence, analyzes pathology to provide critical clinical insights. The newly published study demonstrates that Vesta Risk Stratify biomarkers accurately predicts recurrence and disease progression and outperforms existing guideline-based risk stratification, offering a transformative step forward in precision oncology for bladder cancer. Vesta allows for tailored management based on a patient’s individual risk.

“HGTa tumors carry differing risks as current guidelines attempt to address, and clinical factors such as tumor focality and size can help delineate the true nature of these tumors. These clinical factors, however, are somewhat crude and can be misleading at times. This study demonstrated that CHAI biomarkers can offer improved and additional risk stratification that can go beyond traditional risk factors to better prognosticate outcomes in this population.” - Dr. Sam S. Chang, Chief Surgical Officer, Vanderbilt Ingram Cancer Center

"The ability to derive clinically meaningful predictive and prognostic information from routinely-collected pathology is a paradigm shift for the risk stratification of bladder cancer patients." - Dr. Siamak Daneshmand, Professor of Urology and Medicine (Oncology), and Director of Urologic Oncology, University of Southern California

The multi-center validation study was conducted in collaboration with leading academic centers and underscores both the reproducibility and robustness of the CHAI biomarkers. These findings further establish Vesta as a leading precision oncology platform in the management of non-muscle-invasive bladder cancer.

“This publication is a testament to the clinical significance and scientific rigor of our work,” said Anirudh Joshi, CEO of Valar Labs. “Vesta’s prognostic and predictive tests represent a leap forward in precision medicine for bladder cancer—providing physicians and patients with data-driven insights to guide treatment decisions more effectively.”

“This impactful work continues to build on Vesta’s evidence base as the leading predictive and prognostic biomarker portfolio in bladder cancer. We are excited for patients and providers to benefit from this technology,” said Viswesh Krishna, CTO of Valar Labs.

Valar Labs continues to expand its suite of AI-driven diagnostic tests under the Vesta portfolio and beyond, aiming to improve outcomes across a range of cancers. For more information or to access the full study, please visit https://authors.elsevier.com/c/1lFoD14kpm0hjq.

About Valar Labs

Valar Labs is a precision medicine company developing computational histology AI diagnostic tests for predicting response to cancer therapies. Our mission is to provide every patient and physician the ability to select the best treatment based on the patient's tumor biology. Vesta is our portfolio of diagnostic tests that predicts which patients are unlikely to benefit from BCG therapy and provides detailed risk stratification for recurrence and progression. Vesta BCGPredict and Vesta Risk Stratify HG are clinically available through our CLIA-certified laboratory in Houston, Texas and can be ordered online. For more information, please visit www.valarlabs.com and follow us on LinkedIn and X.

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