Predictive Oncology Q2 2025 Earnings Report

Predictive Oncology EPS Results

• Actual EPS: -$3.30
• Consensus EPS: -$1.35
• Beat/Miss: Missed by -$1.95
• One Year Ago EPS: N/A

Predictive Oncology Revenue Results

• Actual Revenue: $0.00 million
• Expected Revenue: $1.50 million
• Beat/Miss: Missed by -$1.50 million
• YoY Revenue Growth: N/A

Predictive Oncology Announcement Details

• Quarter: Q2 2025
• Date: 8/13/2025
• Time: Before Market Opens
• Conference Call Date: Thursday, August 14, 2025
• Conference Call Time: 7:00AM ET

Predictive Oncology (NASDAQ:POAI), Inc. is a biotechnology company that leverages artificial intelligence and digital biology to support drug discovery and development in oncology. Its core business revolves around the application of machine learning algorithms to high-content cellular imaging, multi-omic profiling, and clinical response data. By integrating these diverse data streams, the company aims to generate predictive models that forecast the efficacy and toxicity of candidate therapeutics, thereby accelerating preclinical decision-making and reducing development timelines.

The company’s primary offerings include its Phenomics platform, which combines automated microscopy with advanced image analysis to capture subtle phenotypic changes in cancer cells. This platform is complemented by proprietary data integration tools that correlate cellular phenotypes with genetic and molecular profiles. Predictive Oncology also provides custom assay development and contract research services to pharmaceutical and biotech partners seeking to validate drug mechanisms, optimize dosing regimens, or identify novel targets in oncology and related therapeutic areas.

Headquartered in St. James, New York, Predictive Oncology serves a global customer base that includes large pharmaceutical companies, emerging biotechs, and academic research institutions. The company began trading on the Nasdaq Capital Market under the ticker POAI in December 2020. Its leadership team brings together expertise in computational biology, oncology research, and data science, positioning Predictive Oncology at the intersection of cutting-edge technology and translational cancer research.