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Scientific analysis and mathematical modeling of clinical research data

Awarded
75N98026Q00752Federal

Contract Overview

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

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This contract solicits scientific analysis and mathematical modeling of clinical research data under a Total Small Business Set-Aside (FAR 19.5), exclusively available to small businesses, with NAICS code 541690. The work requires development and validation of signal processing models to correlate SPG waveform features with cardiovascular function markers, demonstrate superior performance of SPG+PPG models over PPG-only approaches for noninvasive blood pressure estimation, and provide mechanistic interpretations of SPG signal origins in relation to cardiovascular physiology. The project is structured around six deliverables including a project plan, signal processing pipeline, clinical correlation report, blood pressure estimation validation, real-time demonstration package, and a final technology transfer report. The contract is awarded on a Firm Fixed Price basis using a Lowest Price Technically Acceptable (LPTA) evaluation methodology, where proposals must first pass two mandatory pass/fail gates: technical acceptability and acceptable or neutral relevant experience/past performance. Offerors must submit an eight-page combined narrative divided into two volumes—five pages for technical approach and three for past performance—and a separate pricing file detailing cost per deliverable. Compliance with stringent data security protocols is required, including use of FedRAMP Moderate or higher cloud infrastructure for Controlled Unclassified Information, adherence to HIPAA and HHS regulations, secure coding practices, and reliance solely on de-identified data provided by the government. All deliverables must meet exact reproducibility and accuracy standards, such as systolic and diastolic blood pressure estimation errors of no more than 7 mmHg and 5 mmHg respectively on holdout datasets, end-to-end latency under 100 ms at 60 Hz sampling, and code quality meeting agency standards. The contract duration is 12 months from award with biweekly emails, monthly calls, and quarterly written reports required, and the final report and technology transfer package due at month 12. The Offeror must include completed representations per FAR 52.212-3, resumes of key personnel including a Principal Investigator and senior scientist, and a detailed Minimum Performance Standards Checklist with cross-references. Proposals are due by July 17, 2026, at 11:00 PM EDT, with the contract administered by David Shen of the National Institutes of Health in Bethesda, Maryland.

General Info

NIH seeks small businesses for clinical data modeling in Bethesda, Maryland, by July 18, 2026, via SAM.gov.

Contract Value

$202,000

NAICS

541690 - Other Scientific and Technical Consulting Services

Place of Performance

Bethesda, MD, 20892, USA

Set-Aside

SBA

Award Issued Date

Documents

4

Evaluation Criteria and Instructions for Optical Cardiovascular Monitoring LPTA

PDF, High priority: read this first6 pages · evaluation-criteria
High

Solicitation 75N98026Q00752 Scientific analysis and mathematical modeling of clinical research data

PDF, High priority: read this first4 pages · rfq
High

Statement of Work for Optical Cardiovascular Monitoring Project

PDF, High priority: read this first5 pages · sow
High

FAQ - Scientific Analysis and Mathematical Modeling of Clinical Research Data

PDF, Medium priority8 pages · q-and-a
Medium

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Timeline

1 update
PhaseAwarded
Posted

Combined Synopsis

Notice updated

Response deadline changed from Jul 18, 2026 to Jul 21, 2026. The notice description changed.

Awarded

Contract was awarded

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Organization & Contact Information

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AgencyDepartment Of Health And Human Services → National Institutes Of Health Olao
Contacts1 person available
OfficeBETHESDA, MD, 20892, USA
Office AddressBETHESDA, MD, 20892, USA
Contacts

Full Description

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Advancing Robust Optical Cardiovascular Monitoring via SPG and PPG

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