Absci (NASDAQ:ABSI) Issues Quarterly Earnings Results

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

Absci Stock Performance

ABSI traded down $0.13 on Tuesday, reaching $3.08. The company had a trading volume of 4,490,830 shares, compared to its average volume of 6,110,506. Absci has a fifty-two week low of $2.45 and a fifty-two week high of $6.72. The stock has a market cap of $353.76 million, a P/E ratio of -3.31 and a beta of 2.09. The company’s fifty day moving average is $3.87 and its 200 day moving average is $3.69. The company has a debt-to-equity ratio of 0.01, a quick ratio of 5.63 and a current ratio of 5.63.

Analysts Set New Price Targets

Several research firms have recently weighed in on ABSI. HC Wainwright restated a “buy” rating and set a $7.00 price objective on shares of Absci in a research note on Friday, January 17th. Guggenheim restated a “buy” rating and set a $10.00 price objective on shares of Absci in a research note on Tuesday, December 3rd. Needham & Company LLC began coverage on shares of Absci in a research note on Wednesday, January 22nd. They set a “buy” rating and a $9.00 price objective on the stock. Finally, KeyCorp lowered their price objective on shares of Absci from $6.00 to $5.00 and set an “overweight” rating on the stock in a research note on Wednesday, January 8th. Seven research analysts have rated the stock with a buy rating, According to MarketBeat.com, Absci presently has an average rating of “Buy” and a consensus target price 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.