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FAR Updated to Conform with Prior SBA Changes to its Regulations

Client Alert | 1 min read | 09.16.21

On August 11, 2021, the Department of Defense, General Services Administration, and National Aeronautics and Space Administration issued two final rules updating the Federal Acquisition Regulation to implement provisions from past National Defense Authorization Acts that the Small Business Administration has already implemented in its own regulations. 

In 2016, the SBA implemented the new statutorily-required limitations on subcontracting at 13 C.F.R. § 125.6.  Effective September 10, 2021, FAR part 19 now reflects the new methodology for calculating compliance with the limitations on subcontracting.  For contracts that are set-aside or awarded on a sole source basis due to size and/or status, the contractor may not subcontract more than a certain percentage of the work to subcontractors that are not similarly situated.  The final rule revises FAR 52.219-14 as well as adds a new clause, FAR 52.219-33, regarding the nonmanufacturer rule.

In 2019, the SBA updated 13 C.F.R. § 125.3 to provide further direction to contracting officers on what it means for a contractor to make a good faith effort to comply with a small business subcontracting plan and to require that goals in commercial subcontracting plans include indirect costs.  Effective September 10, 2021, the final rule updates FAR part 19 to conform to these changes.

To read in-depth analyses about the limitations on subcontracting final rule click here and good faith efforts in subcontracting click here.

Insights

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 .  ...