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Section 809 Panel Weighs in on Ways to Modernize the Board of Contract Appeals

Client Alert | 1 min read | 02.01.19

In the Section 809 Panel’s third and final volume of its report, the panel urged Congress to require contractors and contracting officers to use electronic case management system (ECMS) for the Boards of Contract Appeals and to permit the boards to collect user fees to pay for the upkeep of the system. The panel used the Armed Services Board of Contract Appeals (ASBCA) as a case study citing to voluminous records and an uptick in cases since 2009 as a reason to require the use of an ECMS.

The panel also urged Congress to increase the thresholds for accelerated and expedited appeals before the Board of Contract Appeals. The panel noted that the thresholds established in the Contract Disputes Act of 1978 were amended once in 1994 and have not been amended since. The panel recommends the following increased thresholds: (1) $250,000 threshold for accelerated procedures for all businesses (previously $100,000); and (2) $150,000 threshold for expedited procedures (previously $50,000) or $250,000 for small business concerns (previously $150,000). The time period for the boards to issue decisions under the accelerated and expedited procedures would remain unchanged. The panel recommended requiring threshold review every five years to mirror the requirement for other acquisition-related thresholds. 

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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 .  ...