Absci (NASDAQ:ABSI) Announces Quarterly Earnings Results

Absci (NASDAQ:ABSI) announced its quarterly earnings data on Tuesday. The company reported ($0.25) earnings per share (EPS) for the quarter, missing analysts’ consensus estimates of ($0.23) by ($0.02), Zacks reports. Absci had a negative net margin of 2,321.56% and a negative return on equity of 46.56%.

Absci Price Performance

Shares of Absci stock traded down $0.13 on Tuesday, reaching $3.09. The stock had a trading volume of 3,885,240 shares, compared to its average volume of 2,345,240. The business’s 50 day moving average is $3.87 and its two-hundred day moving average is $3.69. The company has a market cap of $354.33 million, a P/E ratio of -3.32 and a beta of 2.09. Absci has a 1 year low of $2.45 and a 1 year high of $6.72. The company has a current ratio of 5.63, a quick ratio of 5.63 and a debt-to-equity ratio of 0.01.

Analyst Upgrades and Downgrades

A number of brokerages have recently commented on ABSI. Needham & Company LLC assumed coverage on Absci in a research report on Wednesday, January 22nd. They set a “buy” rating and a $9.00 price target on the stock. KeyCorp dropped their price objective on shares of Absci from $6.00 to $5.00 and set an “overweight” rating on the stock in a report on Wednesday, January 8th. HC Wainwright reiterated a “buy” rating and issued a $7.00 target price on shares of Absci in a research note on Friday, January 17th. Finally, Guggenheim restated a “buy” rating and set a $10.00 price target on shares of Absci in a research note on Tuesday, December 3rd. Seven analysts have rated the stock with a buy rating, Based on data from MarketBeat, the stock has an average rating of “Buy” and a consensus price target of $8.57.

Absci Company Profile

Absci Corporation operates as a data-first generative artificial intelligence (AI) drug creation company in the United States. The company combines AI with scalable wet lab technologies to create biologics for patients. Its integrated drug creation platform is designed to improve upon traditional biologic drug discovery by using AI to simultaneously optimize multiple drug characteristics that may be important to development and therapeutic benefit.