logo
logo

GSK Shareholder Alert: Lawsuit Against Misleading Statements

Business and Finance
‌
‌
sparksAI summary
Display highlights
  • Class action lawsuit filed against GSK plc by Bronstein, Gewirtz & Grossman, LLC
  • Focus on misleading statements by GSK regarding Zantac and cancer risks
  • Investors with losses can join the case until April 7, 2025
  • Representation on a contingency fee basis by the law firm
360 summary
  • Investors who suffered a loss in Merck have until April 14, 2025, to request that the Court appoint them as lead plaintiff in the class action lawsuit.
  • There is no cost to investors to join the lawsuit, as Bronstein, Gewirtz & Grossman, LLC represents investors on a contingency fee basis.
  • The law firm has a track record of recovering hundreds of millions of dollars for investors in securities fraud class actions and shareholder derivative suits.
Business InsiderBusiness Insider
  • If you suffered a loss in GSK or Trade Desk, you have until April 7, 2025, or April 21, 2025, respectively, to request that the Court appoint you as lead plaintiff.
  • Your ability to share in any recovery doesn't require that you serve as lead plaintiff, providing an opportunity for all affected investors to participate in potential damages recovery.
  • Bronstein, Gewirtz & Grossman, LLC operates on a contingency fee basis, seeking reimbursement only if successful in recovering damages, ensuring no upfront costs for investors involved in the class action lawsuits.
Business InsiderBusiness Insider
Explore
The above information is compiled by Business Insider and does not represent any position of Arbor. It does not constitute any investment advice made by Arbor. Before making any investment decisions, investors should consider the risk factors related to the investment products based on their own circumstances and seek advice from professional investment advisors if necessary. We strive to ensure but cannot guarantee the truthfulness, accuracy, and originality of the above content, and we make no promises or guarantees in this regard. As machine learning has a probabilistic nature, it may lead to incorrect reflection of facts in certain situations. You should appropriately evaluate the accuracy of any information summary based on your usage, including through manual evaluation of the information summary. We are not responsible for any losses or liabilities incurred by you due to your use, viewing, and access of the platform or failure to do so.
mobile

Remove Duplicated Information

app-iconLess is More
app-icon
Applicable for iOS and Android systems
Follow Us
logo
All rights reserved © 2025 Arbor.