On May 21, 2026 Agenus Inc. (Nasdaq: AGEN), a leader in immuno-oncology innovation, reported new retrospective data showing that Noetik’s artificial intelligence-based TARIO-2 model identified spatial tumor microenvironment patterns associated with clinical outcomes from routine pretreatment tumor pathology images in patients treated with botensilimab (BOT) plus balstilimab (BAL), Agenus’ investigational next-generation multifunctional, Fc-enhanced anti-CTLA-4 and anti-PD-1 immunotherapy combination.

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The data will be presented on May 30, 2026, by Ryan Dalton, Ph.D., of Noetik, during a poster session at the 2026 American Society of Clinical Oncology (ASCO) (Free ASCO Whitepaper) Annual Meeting. The presentation, titled "Artificial intelligence foundation model as a predictor of efficacy of next-generation checkpoint inhibition with botensilimab (BOT) + balstilimab (BAL) in solid tumors using pretreatment H&E images," evaluated whether Noetik’s TARIO-2 model could analyze standard hematoxylin and eosin (H&E) pathology images to identify spatial tumor microenvironment patterns associated with clinical outcomes following treatment with BOT+BAL.

BOT is an Fc-enhanced anti-CTLA-4 antibody designed to broaden anti-tumor immune activity through effects on T-cell priming, antigen presentation and regulatory T cells within the tumor microenvironment. Given BOT+BAL’s differentiated mechanism and prior observations that clinical activity is not strongly associated with traditional biomarkers such as PD-L1 expression or tumor mutational burden, broader tumor microenvironment-based approaches may be important for identifying patients most likely to benefit.

The analysis included 113 efficacy-evaluable patients treated with BOT+BAL in the C-800-01 Phase 1b trial who had available pretreatment H&E images. Tumor cohorts included microsatellite stable (MSS) metastatic colorectal cancer (mCRC) without active liver metastases, ovarian cancer and sarcomas. The analysis evaluated TARIO-2’s ability to predict clinical endpoints including best overall response and overall survival.

In the MSS mCRC without active liver metastases cohort, TARIO-2 demonstrated statistically significant predictive performance for both best overall response and overall survival. Supportive trends were observed in the ovarian cancer and sarcoma cohorts. In the MSS mCRC without active liver metastases cohort, TARIO-2 also outperformed benchmark pathology foundation models in predicting best overall response and overall survival.

TARIO-2 does not rely on a traditional single-marker biomarker approach. Instead, the model applies AI-based spatial tumor microenvironment analysis to standard H&E pathology images, which are routinely generated during cancer diagnosis and clinical evaluation. By using widely available H&E images, TARIO-2 is designed to extract biologically relevant tumor microenvironment features without requiring more complex tissue-profiling approaches that may be difficult to implement routinely. This approach may support future patient stratification strategies if prospectively validated.

"Routine pathology images are already part of cancer care, but much of the biologic information they contain is difficult to interpret by eye alone," said Ryan Dalton, Ph.D., Senior Computational Scientist at Noetik. "These data suggest that AI-based analysis of pretreatment H&E images may help identify spatial tumor microenvironment patterns associated with clinical benefit from BOT+BAL. The findings support prospective validation of TARIO-2 as a practical, image-based biomarker strategy."

BOT+BAL is being evaluated as a novel immunotherapy combination designed to expand immune activity in tumors that have historically been difficult to treat with conventional immunotherapies. The ability to better understand which patients are most likely to benefit remains an important area of translational research, particularly in tumor types with limited immunotherapy options.

"BOT+BAL is designed to engage the immune system in tumors that have historically been resistant to conventional immunotherapy, through differentiated mechanisms not fully captured by traditional biomarkers such as PD-L1 expression or tumor mutational burden," said Dhan Chand, Ph.D., Vice President of Research at Agenus. "These data represent an important step toward aligning BOT+BAL’s differentiated biology with the patients most likely to benefit. Prospective validation will be an important next step as we continue to advance BOT+BAL clinical development."

The findings support prospective validation of TARIO-2 as an H&E-based biomarker strategy for BOT+BAL, including further evaluation in MSS colorectal cancer and broader solid tumor datasets.

Following the poster session on May 30, 2026, the full poster will be available on the Publications page of the Agenus website.

Presentation Details

Abstract Title: Artificial intelligence (AI) foundation model as a predictor of efficacy of next-generation checkpoint inhibition with botensilimab (BOT) + balstilimab (BAL) in solid tumors using pretreatment H&E images
Abstract No.: 2535
Presenter: Ryan Dalton Ph.D., Sr. Computational Scientist, Noetik
Session Title: Poster Session – Developmental Therapeutics—Immunotherapy
Location: Hall A – Posters and Exhibits
Poster Board: 325
Date/Time: May 30, 2026, 1:30 PM–4:30 PM CDT

(Press release, Agenus, MAY 21, 2026, View Source [SID1234665972])