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Merely Identifying Each Element Of A Claim In The Prior Art Is Insufficient To Establish Unpatentability

Client Alert | 1 min read | 12.13.06

In Sanofi-Synthelabo et al v. Apotex, Inc. et al (No. 06-1613; Dec. 8, 2006), the Federal Circuit affirms a district court's granting of a preliminary injunction, holding that Apotex failed to establish a likelihood of proving, inter alia, the patent invalid as obvious over the prior art. Sanofi sued Apotex on a patent claim directed to a particular enantiomer of MATTPCA (clopidogrel bisulfate) and requested that the district court grant preliminary injunction to prevent Apotex from marketing its generic clopidogrel bisulfate product. In challenging the “likelihood of success on the merits”, Apotex argued, inter alia , that the claim at issue was rendered obvious by another patent.

In affirming, the Federal Circuit panel upholds the district court's determination that “nothing existed in the prior art that would make pursuing the enantiomer of MATTPCA an obvious choice, particularly in light of the unpredictability of the pharmaceutical properties of the enantiomers and the potential for enantiomers to racemize in the body.” The Court continues: “it is insufficient to merely identify each element in the prior art to establish unpatentability… a party must articulate the reasons why one of ordinary skill in the art would have been motivated to select the references and combine them to render the claimed invention obvious.”

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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. ...