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Patient Preference Information (PPI) Quantification Studies

Active
Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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This contract involves designing and conducting studies to measure patient preferences in clinical decision-making, with a particular focus on rare diseases. The work will employ structured survey techniques alongside statistical methodologies to quantitatively assess how patients weigh different treatment options and outcomes, providing valuable insights to inform regulatory and healthcare decisions. The contract is a subcontract managed by the FDA Office of Acquisitions and Grants Services under the Department of Health and Human Services, with the place of performance in Silver Spring, Maryland. The effort falls under the NAICS code 541611, which pertains to administrative management and general management consulting services. The project aims to enhance understanding of patient perspectives to support more patient-centered healthcare and regulatory processes.

General Info

Design and conduct patient preference studies on rare diseases using surveys for regulatory insights.

NAICS

541611 - Administrative Management and General Management Consulting Services

Place of Performance

Silver Spring, MD, 20993, USA

Set-Aside

NONE

Documents

This scope was carved out of FDABAA-25-00123_Award.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

FY25 FDA Broad Agency Announcement (BAA) for Advanced Research and Development of Regulatory Science

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Timeline

Posted

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Organization & Contact Information

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AgencyDepartment Of Health And Human Services → FDA Office Of Acquisitions And Grants Services
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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Design and execute studies to quantify patient preferences in clinical decision-making, particularly for rare diseases, using structured survey and statistical methods.

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