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Clinical Data Coordination and QA Auditing

Active
Federal

Contract Overview

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The Clinical Data Coordination and QA Auditing subcontract supports the National Institutes of Health NICHD within the Department of Health and Human Services. The primary objective is to ensure data accuracy and quality for prime contractors managing high-risk randomized clinical trials. Key responsibilities include performing quality assurance auditing for approximately 50 clinical sites, monitoring the reporting of adverse events, and providing essential training for site data coordinators. To maintain regulatory compliance, all work must adhere to GCP, GLP, and OHRP Federal Wide Assurance standards. The successful contractor is expected to deliver validated clinical datasets, certified data coordinators, and detailed data audit reports. This opportunity is categorized under NAICS code 541611, with a response deadline set for December 18, 2026.

General Info

QA auditing and data coordination for NIH NICHD clinical trials by December 18, 2026.

NAICS

541611 - Administrative Management and General Management Consulting Services

Place of Performance

MD, USA

Set-Aside

NONE

Documents

This scope was carved out of 75N94026R00008.

The full solicitation package (4 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Best Pharmaceuticals for Children Act Data Coordination Center

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Organization & Contact Information

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AgencyDepartment Of Health And Human Services → National Institutes Of Health Nichd
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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Monitors data accuracy and quality for prime contractors on NIH/NICHD clinical trials. Performs QA auditing for approximately 50 clinical sites, trains site data coordinators, and monitors adverse event reporting. Requires adherence to GCP, GLP, and OHRP Federal Wide Assurance (FWA) standards for high-risk randomized trials. Delivers data audit reports, certified coordinators, and validated clinical datasets.

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