Absci (NASDAQ:ABSI) Releases Quarterly Earnings Results, Misses Estimates By $0.05 EPS

Absci (NASDAQ:ABSI) released its quarterly earnings data on Tuesday. The company reported ($0.24) earnings per share for the quarter, missing the consensus estimate of ($0.19) by ($0.05), Zacks reports. The firm had revenue of $1.70 million for the quarter, compared to analyst estimates of $1.77 million. Absci had a negative return on equity of 45.94% and a negative net margin of 2,321.56%. During the same quarter in the prior year, the firm earned ($0.24) earnings per share.

Absci Price Performance

ABSI stock traded down $0.12 during trading on Thursday, hitting $3.02. 3,284,570 shares of the company’s stock traded hands, compared to its average volume of 1,334,200. Absci has a 52 week low of $1.29 and a 52 week high of $6.72. The stock has a market capitalization of $342.38 million, a price-to-earnings ratio of -3.24 and a beta of 2.18. The company has a debt-to-equity ratio of 0.01, a quick ratio of 6.49 and a current ratio of 6.49. The business has a fifty day simple moving average of $3.94 and a 200 day simple moving average of $4.07.

Analyst Ratings Changes

ABSI has been the subject of a number of research analyst reports. Guggenheim assumed coverage on shares of Absci in a research report on Wednesday, October 2nd. They set a “buy” rating and a $10.00 price objective for the company. HC Wainwright reiterated a “buy” rating and issued a $7.00 price objective on shares of Absci in a research note on Wednesday. Six equities research analysts have rated the stock with a buy rating, According to data from MarketBeat, the company currently has a consensus rating of “Buy” and an average price target of $8.67.

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.