Predictive Oncology (NASDAQ:POAI) Stock Passes Below Two Hundred Day Moving Average – What’s Next?

Predictive Oncology Inc. (NASDAQ:POAI)’s stock price crossed below its 200-day moving average during trading on Wednesday . The stock has a 200-day moving average of $9.57 and traded as low as $2.62. Predictive Oncology shares last traded at $2.69, with a volume of 24,372 shares.

Analyst Ratings Changes

A number of research analysts recently weighed in on POAI shares. Wall Street Zen downgraded Predictive Oncology to a “strong sell” rating in a research note on Saturday, December 6th. Weiss Ratings reissued a “sell (e+)” rating on shares of Predictive Oncology in a research report on Wednesday, October 8th. One investment analyst has rated the stock with a Sell rating, According to data from MarketBeat.com, the stock presently has a consensus rating of “Sell”.

Predictive Oncology Stock Performance

The stock has a market capitalization of $9.13 million, a price-to-earnings ratio of -0.20 and a beta of 1.35. The company’s 50 day moving average is $5.82 and its 200 day moving average is $9.57.

Predictive Oncology (NASDAQ:POAI) last posted its quarterly earnings data on Friday, November 14th. The medical instruments supplier reported ($4.52) earnings per share (EPS) for the quarter, missing the consensus estimate of ($1.35) by ($3.17). Predictive Oncology had a negative return on equity of 732.73% and a negative net margin of 5,065.23%.The company had revenue of $0.00 million for the quarter, compared to the consensus estimate of $1.50 million. On average, equities research analysts anticipate that Predictive Oncology Inc. will post -2.08 earnings per share for the current fiscal year.

About Predictive Oncology

Predictive Oncology, 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.