"Excessive" Pass-Through Charges Defined And Prohibited
Client Alert | 1 min read | 10.15.09
Implementing statutory requirements, FAR has been amended with interim rules (74 Fed. Reg. 52852 (Oct. 14, 2009)) that prohibit "excessive" pass-through charges on cost-reimbursement contracts with civilian agencies in excess of the simplified acquisition threshold and on all types of contracts with DOD in excess of $650,0000 (except for fixed-price contracts awarded based on adequate price competition or for commercial items), to require that the provisions be flowed down to subcontractors, to require that covered contractors and subcontractors report specific information about pass-through charges (indirect costs and profit) either in their proposals when they intend to subcontract more than 70 percent of the contract or subcontract effort or after award when they actually subcontract more than 70 percent of the effort, and to provide that excessive pass-throughs are "unallowable" on flexibly-priced contracts and justify a price adjustment when included in the price of fixed-price contracts. "Excessive" pass-through charges exist when a covered prime contractor or higher-tier subcontractor adds no or negligible value and charges indirect costs or profit (other than indirect costs and profit for managing the subcontractor) on work performed by a subcontractor and the contracting officer makes a determination that the pass-through costs are excessive, normally in evaluating the proposal, but also in evaluating information that contractors and subcontractors are required to report after award when subcontracting plans change sufficiently to exceed the 70 percent reporting threshold.
Insights
Client Alert | 9 min read | 10.21.26
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 .
Client Alert | 2 min read | 10.21.26
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Private Investigations Act Series: Temporal, material and territorial scope
Client Alert | 7 min read | 10.21.26
