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Asset logo for symbol RGEN
Asset logo for symbol RGEN



AI Deep-Learning Forecast (RGEN)

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

Repligen (RGEN) Stocklytics Forecast

Repligen Corp (RGEN) is a leading bioprocessing company that specializes in providing innovative solutions for the life sciences industry. The company has a strong track record of developing and commercializing products that enable the production of biologic drugs. With its focus on improving efficiency and productivity, Repligen Corp has positioned itself as a key player in the bioprocessing market.

When it comes to predicting the stock price of Repligen Corp, there are several factors to consider. One of the key indicators is the company's financial performance. By analyzing its revenue growth, profitability, and overall financial health, analysts can make predictions about the future stock price. Additionally, market trends and industry outlooks also play a significant role in forecasting the stock price of Repligen Corp.

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Frequently Asked Questions

What is the analyst price prediction for Repligen (RGEN) stock?

Analysts have set a target price of $202.67 for Repligen (RGEN), based on forecasts from 27 analysts. The predicted price range extends from a high of $275 to a low of $156. This represents a potential increase of up to 118.39% and a decrease of 23.89% from the current price of $125.92. These forecasts are as of 2022 Jul 20.

What are the analyst ratings for Repligen (RGEN) stock?

The analyst ratings for Repligen (RGEN) are distributed as follows: 5 analysts recommend buying, 1 have a neutral stance, and 0 suggest selling. The prevailing sentiment among the total of 6 analysts leans towards a buy rating. These ratings indicate the general sentiment among the analysts covering Repligen.

What is the AI price prediction for Repligen (RGEN) stock?

At present, there is no AI or machine-learning-based price prediction available for Repligen (RGEN) stock. The lack of a forecast could stem from various factors, such as inadequate data or the necessity for model recalibration.


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