Account

Sign in to access your account and subscription

Calculation of Lost Profits Damages in Patent Cases

Upon a finding of patent infringement, a court is to award the patentee "damages adequate to compensate for the infringement, but in no event less than a reasonable royalty for the use made of the invention by the infringer, together with interest and costs as fixed by the court." 35 U.S.C. '284. In most cases, the patentee will be entitled to a larger damage award if it can recover damages based on lost profits. Lost profits are not, however, available in all cases. This two-part article will review the current state of the law governing the availability of lost profits damages in patent infringement cases in the first part and the calculation of these damages based on diverted sales in the second part.

29 minute read January 28, 2005 at 10:54 AM
By
Michael M. Carlson
Calculation of Lost Profits Damages in Patent Cases

Part One of a Two-Part Series

This premium content is locked for LawJournalNewsletters subscribers only

ENJOY UNLIMITED ACCESS TO THE SINGLE SOURCE OF OBJECTIVE LEGAL ANALYSIS, PRACTICAL INSIGHTS, AND NEWS IN LawJournalNewsletters

  • Stay current on the latest information, rulings, regulations, and trends
  • Includes practical, must-have information on copyrights, royalties, AI, and more
  • Tap into expert guidance from top entertainment lawyers and experts

Already have an account? Sign In Now

For enterprise-wide or corporate access, please contact Customer Service at [email protected] or call 1-877-256-2473.

NOT FOR REPRINT

© 2026 ALM Global, LLC, All Rights Reserved. Request academic re-use from www.copyright.com. All other uses, submit a request to [email protected]. For more information visit Asset & Logo Licensing.

Continue Reading

Adverse Possessor Provided Insufficient Evidence to Support TackingTown’s Installation of Guardrails Did Not Constitute a TakingMortgagee Entitled to Deficiency JudgmentLandowner Adequately Alleged Trespass During Renovation

August 13, 2026

Agentic AI introduces risks that are novel and complex, but the most effective response is a familiar one. Zero Trust answers the problem of when an AI agent misfires on its own by constraining what an agent can do rather than betting on how it will behave.

August 01, 2026