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GANX — Gain Therapeutics News Story

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Gain Therapeutics Q2 net loss per share narrows as R&D expenses fall

Gain Therapeutics Q2 net loss per share narrows as R&D expenses fall


Overview

  • Biotechnology firm's Q2 net loss per share narrowed yr/yr to $0.11

  • R&D expenses fell due to lower costs for lead compound and personnel

  • FDA cleared IND for rexaceract, enabling Phase 2 clinical development


Outlook

  • Company expects to begin Phase 2 trial of rexaceract in Parkinson's disease in Q3 2026

  • Final results from Phase 1b clinical study of rexaceract expected in Q4 2026

  • GT-04686 initial target indication expected to be selected by year end


Result Drivers

  • R&D EXPENSES - Decrease in R&D expenses was mainly due to lower costs for lead program rexaceract and reduced research and development personnel expenses, partially offset by grant expiration and unfavorable currency translation

  • G&A EXPENSES - Increase in general and administrative expenses was due to higher professional fees, personnel costs, and unfavorable currency translation


Company press release: ID:nGNXjff7s


Key Details

Metric

Beat/Miss

Actual

Consensus Estimate

Q2 Loss Per Share

$0.11


Analyst Coverage

  • The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 5 "strong buy" or "buy", no "hold" and no "sell" or "strong sell"

  • The average consensus recommendation for the biotechnology & medical research peer group is "buy"

  • Wall Street's median 12-month price target for Gain Therapeutics Inc is $8.00, about 352% above its August 10 closing price of $1.77


Reuters Recommended Reads

  • Aug 10 - CervoMed Q2 net loss lower than estimates as costs drop

  • Aug 10 - Biohaven Q2 net loss narrows on lower R&D spend

  • Aug 11 - Upstream Bio Q2 net loss narrows slightly on lower R&D costs


For questions concerning the data in this report, contact Estimates.Support@lseg.com. For any other questions or feedback, contact reuters.support@thomsonreuters.com.


(This story was created using Reuters automation and AI based on LSEG and company data. It was checked and edited by a Reuters journalist prior to publication.)

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