Generate Biomedicines (NASDAQ:GENB) Rating Increased to Hold at Wall Street Zen

Wall Street Zen upgraded shares of Generate Biomedicines (NASDAQ:GENB) from a sell rating to a hold rating in a research note published on Saturday morning.

Several other equities research analysts have also issued reports on GENB. Morgan Stanley increased their price objective on shares of Generate Biomedicines from $20.00 to $22.00 and gave the stock an “overweight” rating in a research report on Thursday, May 14th. HC Wainwright lifted their target price on shares of Generate Biomedicines from $16.00 to $25.00 and gave the company a “buy” rating in a report on Friday, May 8th. Six equities research analysts have rated the stock with a Buy rating and one has assigned a Hold rating to the stock. Based on data from MarketBeat.com, the company currently has an average rating of “Moderate Buy” and a consensus target price of $25.40.

Generate Biomedicines Stock Down 3.1%

Shares of NASDAQ:GENB opened at $13.40 on Friday. The business’s 50-day moving average price is $14.34. The stock has a market cap of $1.72 billion and a PE ratio of -12.52. Generate Biomedicines has a 1 year low of $11.00 and a 1 year high of $18.18.

Generate Biomedicines (NASDAQ:GENB) last posted its quarterly earnings results on Thursday, May 7th. The company reported ($1.07) EPS for the quarter, missing the consensus estimate of ($0.48) by ($0.59).

About Generate Biomedicines

Generate Biomedicines, Inc (NASDAQ: GENB) is a biotechnology company that applies machine learning and generative artificial intelligence to the design and discovery of novel therapeutics. The company develops computational platforms to create and optimize protein sequences and biological molecules with the goal of producing new medicines across a range of modalities. Its core activities center on algorithm-driven design, iterative experimental validation, and the translation of computational outputs into candidate therapeutic molecules.

Generate’s technology combines advanced computational models with high-throughput laboratory methods to accelerate discovery and improve the likelihood of producing viable drug candidates.