Erasca Q2 net loss widens on higher R&D costs

Erasca Q2 net loss widens on higher R&D costs


Overview

  • U.S. oncology drug developer's Q2 net loss widened yr/yr on higher R&D expenses

  • Company ended Q2 with $384 mln in cash, cash equivalents, and marketable securities

  • Raised $632 mln in July public offering to support pipeline advancement


Outlook

  • Erasca expects Phase 1 monotherapy expansion data for ERAS-0015 in H1 2027

  • Company anticipates preliminary Phase 1 monotherapy data for ERAS-4001 in H2 2026

  • Erasca expects current cash to fund planned milestones, including key data readouts and trial initiations


Result Drivers

  • CLINICAL TRIAL SPENDING - Higher R&D expenses driven by increased costs for clinical trials, preclinical studies, and discovery activities

  • PIPELINE ADVANCEMENT - Progress in ERAS-0015 and ERAS-4001 programs, including updated clinical data and plans for registration-enabling trials


Company press release: ID:nGNX33y33y


Key Details

Metric

Beat/Miss

Actual

Consensus Estimate

Q2 Net Loss

$44.08 mln

Q2 Loss Per Basic Share

$0.14

Q2 Operating Expenses

$47.62 mln

Q2 Operating Income

-$47.62 mln


Analyst Coverage

  • The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 9 "strong buy" or "buy", 2 "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 Erasca, Inc. is $21.50, about 18.7% above its August 10 closing price of $18.12


Reuters Recommended Reads

  • Aug 11 - Intensity Therapeutics Q2 net loss widens as R&D costs rise

  • Aug 10 - Olema Pharmaceuticals Q2 net loss widens on higher clinical trial spending

  • Aug 11 - Shattuck Labs Q2 net loss widens as R&D spending rises


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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