Absci (ABSI) Projected to Post Earnings on Tuesday

Absci (NASDAQ:ABSI) is expected to be releasing its earnings data after the market closes on Tuesday, March 18th. Analysts expect Absci to post earnings of ($0.23) per share and revenue of $1.77 million for the quarter. Individual interested in listening to the company’s earnings conference call can do so using this link.

Absci Price Performance

Shares of ABSI opened at $3.06 on Tuesday. The company has a debt-to-equity ratio of 0.01, a quick ratio of 5.63 and a current ratio of 5.63. The stock has a 50 day simple moving average of $3.86 and a 200 day simple moving average of $3.74. Absci has a 52-week low of $2.45 and a 52-week high of $6.72. The firm has a market capitalization of $351.46 million, a PE ratio of -3.29 and a beta of 2.09.

Analyst Upgrades and Downgrades

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