Predictive Oncology (NASDAQ:POAI) Share Price Crosses Below 200-Day Moving Average of $2.01

Shares of Predictive Oncology Inc. (NASDAQ:POAIGet Free Report) passed below its 200-day moving average during trading on Thursday . The stock has a 200-day moving average of $2.01 and traded as low as $1.06. Predictive Oncology shares last traded at $1.11, with a volume of 324,449 shares trading hands.

Predictive Oncology Trading Down 6.3 %

The business has a 50 day moving average of $1.22 and a 200-day moving average of $2.00. The stock has a market cap of $4.26 million, a PE ratio of -0.28 and a beta of 1.15.

Predictive Oncology (NASDAQ:POAIGet Free Report) last posted its earnings results on Tuesday, May 14th. The medical instruments supplier reported ($1.04) earnings per share (EPS) for the quarter. Predictive Oncology had a negative net margin of 754.13% and a negative return on equity of 151.51%. The company had revenue of $0.42 million during the quarter.

Institutional Inflows and Outflows

An institutional investor recently bought a new position in Predictive Oncology stock. Carnegie Mellon University purchased a new position in shares of Predictive Oncology Inc. (NASDAQ:POAIFree Report) during the fourth quarter, according to the company in its most recent Form 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 accounts for approximately 0.0% of Carnegie Mellon University’s investment portfolio, making the stock its 5th biggest holding. Carnegie Mellon University owned approximately 0.26% of Predictive Oncology at the end of the most recent quarter. 9.04% of the stock is currently owned by institutional investors.

Predictive Oncology Company Profile

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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.

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