Absci (NASDAQ:ABSI) Price Target Raised to $17.00

Absci (NASDAQ:ABSI) had its price objective raised by investment analysts at Truist Financial from $11.00 to $17.00 in a research report issued to clients and investors on Thursday,Benzinga reports. The firm currently has a “buy” rating on the stock. Truist Financial’s target price would suggest a potential upside of 53.02% from the company’s previous close.

ABSI has been the topic of a number of other reports. HC Wainwright raised their price objective on shares of Absci from $8.00 to $16.00 and gave the company a “buy” rating in a research note on Thursday, June 25th. BTIG Research upped their target price on shares of Absci from $9.00 to $13.00 and gave the company a “buy” rating in a research report on Wednesday, June 24th. Weiss Ratings reiterated a “sell (d-)” rating on shares of Absci in a research report on Monday, April 20th. Morgan Stanley reissued a “positive” rating and issued a $10.00 price target on shares of Absci in a research note on Thursday, June 25th. Finally, Wall Street Zen upgraded Absci from a “sell” rating to a “hold” rating in a research report on Saturday, June 27th. Eight investment analysts have rated the stock with a Buy rating and one has assigned a Sell rating to the stock. Based on data from MarketBeat, the stock currently has an average rating of “Moderate Buy” and a consensus target price of $13.43.

Absci Stock Performance

Shares of ABSI opened at $11.11 on Thursday. The business’s fifty day moving average price is $6.42 and its two-hundred day moving average price is $4.23. The firm has a market capitalization of $1.73 billion, a price-to-earnings ratio of -13.39 and a beta of 2.31. Absci has a 52 week low of $2.24 and a 52 week high of $12.06.

Absci (NASDAQ:ABSI) last announced its quarterly earnings data on Thursday, May 7th. The company reported ($0.19) EPS for the quarter, topping analysts’ consensus estimates of ($0.20) by $0.01. The firm had revenue of $0.21 million during the quarter, compared to analyst estimates of $1.39 million. Absci had a negative return on equity of 66.32% and a negative net margin of 6,450.76%. As a group, research analysts forecast that Absci will post -0.71 EPS for the current year.

Institutional Investors Weigh In On Absci

Several hedge funds have recently bought and sold shares of the company. Quarry LP acquired a new position in shares of Absci in the 3rd quarter valued at $26,000. Essential Partners LLC increased its position in shares of Absci by 113,850.0% in the 1st quarter. Essential Partners LLC now owns 9,116 shares of the company’s stock valued at $27,000 after buying an additional 9,108 shares in the last quarter. BNP Paribas Financial Markets raised its stake in Absci by 91.2% during the 2nd quarter. BNP Paribas Financial Markets now owns 11,287 shares of the company’s stock worth $29,000 after buying an additional 5,385 shares during the period. Legal & General Group Plc raised its stake in Absci by 45.9% during the 2nd quarter. Legal & General Group Plc now owns 11,690 shares of the company’s stock worth $30,000 after buying an additional 3,678 shares during the period. Finally, Principal Financial Group Inc. bought a new position in Absci during the first quarter worth about $31,000. 52.05% of the stock is currently owned by institutional investors and hedge funds.

Absci Company Profile

Absci Corporation (NASDAQ: ABSI) is a biotechnology company that applies machine learning, synthetic biology and automation to accelerate the discovery and development of protein-based therapeutics. The company’s Integrated Drug Creation® (IDC®) platform is designed to identify and produce novel antibody and enzyme candidates at speeds and scales that traditional biopharma discovery methods cannot match. Absci works with pharmaceutical and biotechnology partners to generate, screen and optimize protein molecules for a wide range of therapeutic applications.

The core of Absci’s offering is its end-to-end discovery engine, which combines proprietary algorithms, high-throughput laboratory automation and a deep learning framework.