---
schema_version: "secwatch.filing_event.v1"
accession: "0001171843-24-003176"
form_type: "8-K"
ticker: "AGPU"
cik: "0001446159"
company_name: "Axe Compute Inc."
filed_at: "2024-05-30T23:59:59+00:00"
generated_at: "2026-06-01T07:22:28.491158+00:00"
event_type: "other_material"
sentiment: "positive"
materiality_score: 0.65
calibrated_materiality_score: 0.65
confidence: "high"
source: SEC EDGAR
---

# Predictive Oncology ovarian cancer ML study results positive; to be presented at ASCO 2024

## Summary
- Retrospective study with UPMC Magee-Womens Hospital used 160 multi-omic ML models to predict ovarian cancer survival.
- Seven models achieved high accuracy at two-year threshold; 13 at five-year, outperforming clinical data alone.
- Analysis used data from 2010-2016 including WES, WTS, drug response, and digital pathology profiles.
- Top performing models identified different drivers for short- vs long-term survival, enabling future clinical decision tools.
- Results presented at ASCO Annual Meeting in Chicago, June 3, 2024.

## SEC filing metadata
- accession: 0001171843-24-003176
- form_type: 8-K
- ticker: AGPU
- cik: 0001446159
- company_name: Axe Compute Inc.
- filed_at: 2024-05-30T23:59:59+00:00
- event_type: other_material
- sentiment: positive
- materiality_score: 0.65
- calibrated_materiality_score: 0.65
- confidence: high
- sec_items: 8.01, 9.01
- EDGAR index: https://www.sec.gov/Archives/edgar/data/1446159/000117184324003176/0001171843-24-003176-index.htm
- EDGAR primary document: https://www.sec.gov/Archives/edgar/data/1446159/000117184324003176/f8k_053024.htm

## Machine-readable alternates
- HTML: https://secwatch.observer/filing/0001171843-24-003176
- JSON: https://secwatch.observer/filing/0001171843-24-003176.json
- Plain text: https://secwatch.observer/filing/0001171843-24-003176.txt

This AI-assisted summary is a reading aid. Review the linked SEC EDGAR filing before relying on any specific claim.