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Lacking Disclosure Of An Algorithm For Performing The Recited Computer Function, Means-Plus-Function Claim Is Indefinite

Client Alert | 1 min read | 10.28.08

In Net Moneyin, Inc. v. Verisign, Inc. (No. 07-1565; October 20, 2008), the Federal Circuit affirms a district court's judgment that certain disputed claims were invalid as indefinite under 35 U.S.C. § 112, ¶6, but reverses the summary judgment that another disputed claim was invalid as anticipated by prior art.

The claims related to systems for processing credit card transactions over the Internet. Certain of the claims included means-plus-function limitations. At issue was whether the specification disclosed structure corresponding to the "means for generating an authorization indicia" limitation. Since the specification only disclosed a general purpose computer, without disclosing an algorithm for performing the claimed function, the Court affirms the indefiniteness of the claims.

The Court also clarifies what a reference must show in order to anticipate a claimed invention. As previous Federal Circuit decisions have stated, in order to demonstrate anticipation, the patent challenger must show "that the four corners of a single, prior art document describe every element of the claimed invention." As the Court clarifies in the present case, however, the prior art must disclose all of the elements of the claim "arranged or combined in the same way as in the claim." Because the district court combined two separate examples disclosed in the prior art reference to find all of the claimed elements, the Court reverses the finding of invalidity.

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Client Alert | 7 min read | 09.14.26

AI in Life Sciences: Ten Legal Considerations and Risks of AI Use in Drug Discovery and Development

Over the past several years, the biopharmaceutical industry has embraced artificial intelligence and machine learning (AI/ML) in near lockstep with the pace of AI/ML innovations. Today, industry leaders are using AI/ML to, among other things: discover and assess biological pathways, target chemical structures and sequences; design proteins; model pre-clinical and clinical trials; recruit and screen potential patient populations; evaluate clinical trial results and biomarker data; prepare regulatory filings; and manage supply chains. Deployment of new AI/ML models promises extraordinary advances in pharmaceutical development. However, as with any technological and scientific advances, the use of AI/ML also poses substantial legal risks that life sciences companies need to consider and proactively manage. ...