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Compared To Structural Claim Language, Functional Language More Susceptible To Inherent Anticipation

Client Alert | 1 min read | 09.15.08

In Leggett & Platt, Inc. v. Vutek, Inc. (No. 07-1515; August 21, 2008), the Federal Circuit affirms the district court's summary judgment of invalidity of a patent for a method and apparatus for ink jet printing UV curable ink on a rigid substrate.

The claims of the asserted patent use functional language rather than structural language to describe a cold UV curing assembly, i.e., "the cold UV assembly being effective to impinge sufficient UV light on the ink to substantially cure the ink." The district court had construed the phrase "substantially cure" to mean "cured to a great extent or almost completely cured." Thus, the Federal Circuit concludes that this claim limitation will be anticipated so long as the Light Emitting Diodes ("LEDs") disclosed in the prior art patent are able to cure the ink to a great extent. The prior art does not expressly disclose that its LEDs cure the ink to a great extent, but it does teach that if a UV radiation source is passed over the ink at a slower speed and/or multiple times, the degree to which the ink is cured will increase. This teaching was supported by expert testimony that multiple passes by the disclosed LEDs would eventually result in a substantial cure. Therefore, the Federal Circuit concludes that the prior art inherently discloses LEDs that are "effective to" cure the ink to a great extent, and thus affirms the district court's summary judgment 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. ...