Absci (NASDAQ:ABSI) Issues Earnings Results

Absci (NASDAQ:ABSI) released its quarterly earnings data on Tuesday. The company reported ($0.25) earnings per share (EPS) for the quarter, missing the consensus estimate of ($0.22) by ($0.03), Zacks reports. The company had revenue of $0.67 million for the quarter, compared to the consensus estimate of $1.77 million. Absci had a negative net margin of 2,321.56% and a negative return on equity of 46.56%.

Absci Stock Down 3.2 %

NASDAQ ABSI opened at $2.98 on Thursday. The company has a quick ratio of 5.63, a current ratio of 5.63 and a debt-to-equity ratio of 0.01. The company has a fifty day moving average of $3.87 and a two-hundred day moving average of $3.68. The firm has a market capitalization of $342.27 million, a price-to-earnings ratio of -3.20 and a beta of 2.09. Absci has a 52 week low of $2.45 and a 52 week high of $6.72.

Analyst Upgrades and Downgrades

Several research firms have recently issued reports on ABSI. HC Wainwright reiterated a “buy” rating and set a $7.00 price objective on shares of Absci in a research report on Wednesday. KeyCorp cut their target price on shares of Absci from $6.00 to $5.00 and set an “overweight” rating for the company in a report on Wednesday, January 8th. Guggenheim reissued a “buy” rating and issued a $10.00 target price on shares of Absci in a report on Tuesday, December 3rd. Finally, Needham & Company LLC reissued a “buy” rating and issued a $9.00 target price on shares of Absci in a report on Wednesday. Seven analysts have rated the stock with a buy rating, Based on data from MarketBeat, the company currently has a consensus 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.