Predictive Oncology Inc. Forecasted to Post Q3 2024 Earnings of ($0.32) Per Share (NASDAQ:POAI)

Predictive Oncology Inc. (NASDAQ:POAI) – Investment analysts at HC Wainwright issued their Q3 2024 earnings per share estimates for Predictive Oncology in a research note issued on Monday, August 19th. HC Wainwright analyst S. Ramakanth expects that the medical instruments supplier will earn ($0.32) per share for the quarter. HC Wainwright has a “Buy” rating and a $3.00 price objective on the stock. HC Wainwright also issued estimates for Predictive Oncology’s Q4 2024 earnings at ($0.26) EPS, Q1 2025 earnings at ($0.10) EPS, Q2 2025 earnings at ($0.09) EPS, Q3 2025 earnings at ($0.10) EPS, Q4 2025 earnings at $0.05 EPS, FY2026 earnings at $0.05 EPS, FY2027 earnings at $0.25 EPS and FY2028 earnings at $0.43 EPS.

Predictive Oncology Stock Up 6.1 %

NASDAQ:POAI opened at $0.97 on Tuesday. Predictive Oncology has a 1-year low of $0.85 and a 1-year high of $4.70. The firm’s 50-day moving average price is $1.08 and its 200-day moving average price is $1.80.

Hedge Funds Weigh In On Predictive Oncology

A hedge fund recently bought a new stake in Predictive Oncology stock. Carnegie Mellon University purchased a new position in Predictive Oncology Inc. (NASDAQ:POAI) during the 4th quarter, according to the company in its most recent 13F filing with the Securities and Exchange Commission. The institutional investor purchased 10,358 shares of the medical instruments supplier’s stock, valued at approximately $34,000. Predictive Oncology comprises 0.0% of Carnegie Mellon University’s holdings, making the stock its 5th largest holding. Carnegie Mellon University owned 0.26% of Predictive Oncology as of its most recent filing with the Securities and Exchange Commission. 9.04% of the stock is currently owned by institutional investors.

About Predictive Oncology

Predictive Oncology Inc operates as a science-driven company on the oncology drug discovery. It provides various solutions for the oncology drug development. The company, through the integration of scientific rigor and machine learning, has developed the ability to advance molecules into medicine by introducing human diversity earlier into the discovery process with the pairing of artificial intelligence and the biobank of approximately 150K tumor samples.