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Declarant’s Intentional Misrepresentation Not Remedied By Contradictory Supporting Exhibits

Client Alert | less than 1 min read | 03.26.07

In eSpeed, Inc. v. Brokertec USA, L.L.C., (No. 06-1385; March 20, 2007), the Federal Circuit affirms the district court’s judgment declaring a patent unenforceable due to inequitable conduct. eSpeed submitted three declarations and 1139 pages of supporting exhibits disclosing a prior system implemented by eSpeed. One of the declarations stated that the prior system did not include computer code that implements particular trading rules. The supporting exhibits, however, disclosed that the system included computer code for implementing those trading rules. Rejecting eSpeed’s argument the contradictory supporting exhibits vitiated the materiality of the false statements, the Federal Circuit holds that these false statements left the examiner with the impression that further investigation into the operation of the system was not required.

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Client Alert | 9 min read | 10.21.26

Artificial Intelligence in Life Sciences: Reliability of AI-Generated Evidence in Drug Discovery and Development

The life sciences sector is uniquely vulnerable to the inherent risks of AI-generated evidence in drug development and discovery. This client alert focuses on five core challenges: hallucinations, skewed predictions from unrepresentative training data, the opacity of AI reasoning, input sensitivity that undermines reproducibility, and adversarial manipulation of training data. To address these risks, companies should use experimental validation and human oversight as the common legal and regulatory safety net. This entails among other measures auditing AI outputs, characterizing training data, and structural oversight. Companies also should prepare for evolving frameworks and guidance from the U.S. Food and Drug Administration (FDA) and the European Union (EU) that address use of AI in drug discovery and development .  ...