{"canonical":"https://abierto.us/opportunities/75n95024q00163","key":"75N95024Q00163","url":"https://abierto.us/opportunities/75n95024q00163","title":"Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI","solicitation_number":"75N95024Q00163","notice_type":"a","open":false,"response_deadline":"2024-03-12T13:00:00Z","first_posted":"2024-02-16","last_posted":"2024-03-13","department":"HEALTH AND HUMAN SERVICES, DEPARTMENT OF","subagency":"NATIONAL INSTITUTES OF HEALTH","office":"NATIONAL INSTITUTES OF HEALTH NIDA","naics":"541380","psc":"B524","set_aside":null,"place_state":"MD","place_county":"24510","place_county_name":"City of Baltimore","place_city":"2404000","place_city_name":"Baltimore","winner":"UNIVERSITY OF MARYLAND, COLLEGE PARK","award_amount":"65869.00","publications":[{"notice_id":"643c12f1789e482babc0278b3bcc76df","title":"SOURCES SOUGHT: Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI","solicitation_number":"75N95024Q00163","notice_type":"r","base_type":"r","posted":"2024-02-16","posted_at":null,"due_at":"2024-03-04T14:00:00Z","due_date":"2024-03-04","cancelled":null,"archived":null,"archive_date":"2024-03-19","award_number":null,"awardee_name":null,"amount":null,"link_sam":"https://sam.gov/workspace/contract/opp/643c12f1789e482babc0278b3bcc76df/view","enriched":false,"history":[]},{"notice_id":"4661d0778ec94f0f8452bf6c5a6f6e11","title":"Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI","solicitation_number":"75N95024Q00163","notice_type":"k","base_type":"r","posted":"2024-03-06","posted_at":null,"due_at":"2024-03-12T13:00:00Z","due_date":"2024-03-12","cancelled":null,"archived":null,"archive_date":"2024-03-27","award_number":null,"awardee_name":null,"amount":null,"link_sam":"https://sam.gov/workspace/contract/opp/4661d0778ec94f0f8452bf6c5a6f6e11/view","enriched":false,"history":[]},{"notice_id":"df0bb7c44b7b44d69e4fa171867b1898","title":"Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI","solicitation_number":"75N95024Q00163","notice_type":"a","base_type":"k","posted":"2024-03-13","posted_at":null,"due_at":null,"due_date":null,"cancelled":null,"archived":null,"archive_date":"2024-03-28","award_number":"75N95024P000186","awardee_name":"UNIVERSITY OF MARYLAND, COLLEGE PARK College Park","amount":"65869.00","link_sam":"https://sam.gov/workspace/contract/opp/df0bb7c44b7b44d69e4fa171867b1898/view","enriched":false,"history":[]}],"latest_notice_id":"df0bb7c44b7b44d69e4fa171867b1898","first_type":"r","notices":[{"dates":{"posted":"2024-02-16","response_deadline":{"raw":"2024-03-04T09:00:00-05:00","utc":"2024-03-04T14:00:00Z","date":"2024-03-04","time":"09:00:00","utc_offset_seconds":-18000}},"links":{"sam":"https://sam.gov/workspace/contract/opp/643c12f1789e482babc0278b3bcc76df/view"},"naics":{"codes":["541380"],"primary":"541380"},"title":"SOURCES SOUGHT: Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI","agency":{"office":{"code":"75N950","name":"NATIONAL INSTITUTES OF HEALTH NIDA"},"subtier":{"code":"7529","name":"NATIONAL INSTITUTES OF HEALTH"},"department":{"code":"075","name":"HEALTH AND HUMAN SERVICES, DEPARTMENT OF"},"office_address":{"zip":"20892","city":"Bethesda","state":"MD","country":"USA"},"organization_type":"OFFICE"},"status":{"active":false,"archive_date":"2024-03-19","archive_type":"auto15"},"contacts":[{"name":"Rashiid Cummins","role":"primary","email":"rashiid.cummins@nih.gov"}],"base_type":{"code":"r","label":"Sources Sought"},"notice_id":"643c12f1789e482babc0278b3bcc76df","provenance":{"extract":{"url":"https://s3.amazonaws.com/falextracts/Contract%20Opportunities/Archived%20Data/FY2024_archived_opportunities.csv","etag":"\"d582488fe153a9f11bf629913d176ffc-137\"","fetched_at":"2026-09-16T19:07:39.720164Z","row_sha256":"cc6357c4890f648f2b8bf0d2588acd127a0d93c76942dd51c75439fd3fb2f9aa","last_modified":"2026-09-13T14:47:40Z"},"updated_at":"2026-09-16T19:07:39.720164Z","first_seen_at":"2026-09-16T19:07:39.720164Z"},"description":{"text":"This is a Small Business Sources Sought notice. This is NOT a solicitation for proposals, proposal abstracts, or quotations. The purpose of this notice is to obtain information regarding: (1) the availability and capability of qualified small business sources; (2) whether they are small businesses; HUBZone small businesses; service-disabled, veteran-owned small businesses; 8(a) small businesses; veteran-owned small businesses; woman-owned small businesses; or small disadvantaged businesses; (3) their size classification relative to the North American Industry Classification System (NAICS) code for the proposed acquisition. Your responses to the information requested will assist the Government in determining the appropriate acquisition method, including whether a set-aside is possible. An organization that is not considered a small business under the applicable NAICS code should not submit a response to this notice. This notice is issued to help determine the availability of qualified companies technically capable of meeting the Government requirement and to determine the method of acquisition. It is not to be construed as a commitment by the Government to issue a solicitation or ultimately award a contract. Responses will not be considered as proposals or quotes. No award will be made as a result of this notice. The Government will NOT be responsible for any costs incurred by the respondents to this notice. This notice is strictly for research and information purposes only. Statement of Need and Purpose: The MRI Section of the NIA/IRP (National Institute on Aging/Intramural Research Program) specializes in studies of tissue response to aging, and age-related pathology. As part of our program in brain mapping in particular, NIA has a need to work with emerging methods in harmonic analysis, machine learning, and data fusion. These will become central elements in our work on non-invasive diagnosis of brain tissue pathology and understanding microstructural changes that occur with aging. Background Information and Objective: One of the major open questions in aging research is how the brain and brain stem change with age, and what differentiates between healthy and non-healthy aging. This incorporates the development of age-related pathology and disease, including Alzheimer’s disease. The MRI Section has made major advances over the past several years using data stabilization methods. However, new, even more specialized approaches are being developed in the applied mathematics area for signal analysis. These highly mathematical methods are in the realm of novel neural network architectures and implementations and what may be called “data un-compression”, along with data fusion. We wish to apply these emerging methods to our brain MRI work at the NIA IRP after testing on simulated data. Project Requirements/Salient Characteristics: Develop mathematical models of how neural network architecture and hyperparameter settings contribute to the efficiency of input-layer-regularized neural networks. Based on (1), develop self-regularizing networks for parameter estimation in MR relaxometry and MRI data fusion. Construct graph-matching schemes for heterogeneous data fusion in Magnetic Resonance Imaging and other NMR applications, taking advantage of Laplacian embeddings as efficient feature extractors. Apply the machine learning methods developed in (1-3) to simulated MR relaxometry and imaging data based on input parameters from published brain, muscle and cartilage studies to compare the accuracy and precision of these methods with the state of the art. Anticipated Period of Performance: 3/15/2024 – 8/31/2024 Other Considerations: Key Personnel- (2) Mathematics graduate students with experience in advanced machine learning and their application to image processing problems. Capability Statement/Information Sought: Companies that believe they possess the capabilities to provide the required products or services should submit documentation of their ability to meet each of the project requirements to the Contracting Officer. The capability statement must specifically address each of the project requirements separately. Additionally, the capability statement should include 1) the total number of employees, 2) the professional qualifications of personnel as it relates to the requirements outlined, 3) any contractor GSA Schedule contracts and/or other government-wide acquisition contracts (GWACs) by which all of the requirements may be met, if applicable, and 4) any other information considered relevant to this program. Capability statements must also include the Company Name, Unique Entity ID from SAM.gov, Physical Address, and Point of Contact Information. The response must include the respondents’ technical and administrative points of contact, including names, titles, addresses, telephone and fax numbers, and e-mail addresses. Interested companies are required to identify their type of business, applicable North American Industry Classification System (NAICS) Code, and size standards in accordance with the Small Business Administration. The government requests that no proprietary or confidential business data be submitted in a response to this notice. However, responses that indicate the information therein is proprietary will be properly safeguarded for Government use only. Capability statements must include the name and telephone number of a point of contact having authority and knowledge to discuss responses with Government representatives. Capability statements in response to this market survey that do not provide sufficient information for evaluation will be considered non-responsive. When submitting this information, please reference the solicitation notice number. One (1) copy of the response is required and must be in Microsoft Word or Adobe PDF format using 11-point or 12-point font, 8-1/2” x 11” paper size, with 1” top, bottom, left and right margins, and with single or double spacing. The information submitted must be in and outline format that addresses each of the elements of the project requirement and in the capability statement /information sought paragraphs stated herein. A cover page and an executive summary may be included but is not required. The response is limited to ten (10) page limit. The 10-page limit does not include the cover page, executive summary, or references, if requested. All responses to this notice must be submitted electronically to the Contract Specialist and Contracting Officer. Facsimile responses are NOT accepted. The response must be submitted to Rashiid Cummins, Contracting Officer at e-mail address rashiid.cummins@nih.gov. The response must be received on or before March 4th, 2024, 9:00 AM Eastern Time. “Disclaimer and Important Notes: This notice does not obligate the Government to award a contract or otherwise pay for the information provided in response. The Government reserves the right to use information provided by respondents for any purpose deemed necessary and legally appropriate. Any organization responding to this notice should ensure that its response is complete and sufficiently detailed to allow the Government to determine the organization’s qualifications to perform the work. Respondents are advised that the Government is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted. After a review of the responses received, a presolicitation synopsis and solicitation may be published in Federal Business Opportunities. However, responses to this notice will not be considered adequate responses to a solicitation. Confidentiality: No proprietary, classified, confidential, or sensitive information should be included in your response. The Government reserves the right to use any non-proprietary technical information in any resultant solicitation(s).”","origin":"extract"},"notice_type":{"code":"r","label":"Sources Sought"},"schema_version":1,"solicitation_number":"75N95024Q00163","place_of_performance":{"city":{"name":"Baltimore"},"state":{"code":"MD"},"country":{"code":"USA"}},"product_service_code":"Q301"},{"dates":{"posted":"2024-03-06","response_deadline":{"raw":"2024-03-12T09:00:00-04:00","utc":"2024-03-12T13:00:00Z","date":"2024-03-12","time":"09:00:00","utc_offset_seconds":-14400}},"links":{"sam":"https://sam.gov/workspace/contract/opp/4661d0778ec94f0f8452bf6c5a6f6e11/view"},"naics":{"codes":["541380"],"primary":"541380"},"title":"Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI","agency":{"office":{"code":"75N950","name":"NATIONAL INSTITUTES OF HEALTH NIDA"},"subtier":{"code":"7529","name":"NATIONAL INSTITUTES OF HEALTH"},"department":{"code":"075","name":"HEALTH AND HUMAN SERVICES, DEPARTMENT OF"},"office_address":{"zip":"20892","city":"Bethesda","state":"MD","country":"USA"},"organization_type":"OFFICE"},"status":{"active":false,"archive_date":"2024-03-27","archive_type":"auto15"},"contacts":[{"name":"Rashiid Cummins","role":"primary","email":"rashiid.cummins@nih.gov"}],"base_type":{"code":"r","label":"Sources Sought"},"notice_id":"4661d0778ec94f0f8452bf6c5a6f6e11","provenance":{"extract":{"url":"https://s3.amazonaws.com/falextracts/Contract%20Opportunities/Archived%20Data/FY2024_archived_opportunities.csv","etag":"\"d582488fe153a9f11bf629913d176ffc-137\"","fetched_at":"2026-09-16T19:07:39.720164Z","row_sha256":"92e65441f4fa8516dd116472643a2f9c7dc4950d9870b86b724a6dea4ee054fd","last_modified":"2026-09-13T14:47:40Z"},"updated_at":"2026-09-16T19:07:39.720164Z","first_seen_at":"2026-09-16T19:07:39.720164Z"},"description":{"text":"(i) This is a combined synopsis/solicitation for commercial items prepared in accordance with the format in Subpart 12.6 as supplemented with additional information included in this notice. This announcement constitutes the only solicitation; proposals are being requested and a written solicitation will not be issued. (ii) The solicitation number is 75N95024Q00163 and the solicitation is issued as a request for quotation (RFQ). This acquisition is for a commercial item or service and is conducted under the authority of the Federal Acquisition Regulation (FAR) Part 13—Simplified Acquisition Procedures; FAR Subpart 13.5—Simplified Procedures for Certain Commercial Items; and FAR Part 12—Acquisition of Commercial Items and is not expected to exceed the simplified acquisition threshold. THIS IS A NON-COMPETITIVE (NOTICE OF INTENT) COMBINED SYNOPSIS SOLICITATION TO AWARD A CONTRACT OR PURCHASE ORDER WITHOUT PROVIDING FOR FULL OR OPEN COMPETITION (INCLUDING BRAND-NAME). The National Institute on Drug Abuse (NIDA), Office of Acquisition (OA), on behalf of the National Institute on Aging (NIA), intends to negotiate and award a purchase order without providing for full and open competition (including brand-name) to University of Maryland for Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI. This acquisition is conducted as non-competitive for a commercial item or service and is conducted pursuant to FAR 13.106-(b)(1). (iii) The solicitation document and incorporated provisions and clauses are those in effect through Federal Acquisition Circular (FAC) Number 2024-03, with an effective date February 23, 2024. (iv) The associated NAICS code is 541380 and the small business size standard is $19 million. This requirement has no set-aside restrictions. (v) Statement of Work: See SOW attached. (vi) The Government anticipates award of a firm fixed-price purchase order for this acquisition. The period of performance is 3/15/2024 – 8/31/2024. (vii) The provision at FAR 52.252-1, Solicitation Provisions Incorporated by Reference (Feb 1998), applies to this acquisition. This solicitation incorporates one or more solicitation provisions by reference, with the same force and effect as if they were given in full text. Upon request, the Contracting Officer will make their full text available. The offeror is cautioned that the listed provisions may include blocks that must be completed by the offeror and submitted with its quotation or offer. In lieu of submitting the full text of those provisions, the offeror may identify the provision by paragraph identifier and provide the appropriate information with its quotation or offer. Also, the full text of a solicitation provision may be accessed electronically at these addresses: https://www.acquisition.gov/browse/index/far https://www.hhs.gov/grants/contracts/contract-policies-regulations/hhsar/index.html (End of provision) The following provisions apply to this acquisition and are incorporated by reference: FAR 52.204-7 System for Award Management (OCT 2018) FAR 52.204-16 Commercial and Government Entity Code Reporting (AUG 2020) FAR 52.212-1 Instructions to Offerors--Commercial Items (SEPT 2023) FAR 52.212-3 Offeror Representations and Certifications – Commercial Items (FEB 2024) FAR 52.222-22 Previous Contracts and Compliance Reports (FEB 1999) FAR 52.222-52, Exemption from Application of the Service Contract Labor Standards to Contracts for Certain Services-Certification (May 2014) FAR 52.227-14 Rights in Data-General (MAY 2014) HHSAR 352.239-73 Electronic and Information Technology Accessibility Notice (December 18, 2015) The clause at FAR 52.252-2, Clauses Incorporated by Reference (Feb 1998), applies to this acquisition. This contract incorporates one or more clauses by reference, with the same force and effect as if they were given in full text. Upon request, the Contracting Officer will make their full text available. Also, the full text of a clause may be accessed electronically at these addresses: https://www.acquisition.gov/browse/index/far https://www.hhs.gov/grants/contracts/contract-policies-regulations/hhsar/index.html (End of clause) The following clauses apply to this acquisition and are incorporated by reference: FAR 52.204-13 System for Award Management Maintenance (OCT 2018) FAR 52.204-18 Commercial and Government Entity Code Maintenance (AUG 2020) FAR 52.212-4 Contract Terms and Conditions Commercial Items (NOV 2023) HHSAR 352.222-70 Contractor Cooperation in Equal Employment Opportunity Investigations (December 18, 2015) The following provisions and clauses apply to this acquisition and are incorporated as an attachment. Offerors MUST complete the provisions at 52.204-24 and 52.204-26 and submit completed copies as separate documents with their proposal. FAR 52.204-24 Representation Regarding Certain Telecommunications and Video Surveillance Services or Equipment (NOV 2021) FAR 52.204-26 Covered Telecommunications Equipment or Services-Representation (OCT 2020) FAR 52.212-5, Contract Terms and Conditions Required to Implement Statutes or Executive Orders-Commercial Items (FEB 2024) Invoicing Instructions with IPP (viii) The provision at FAR clause 52.212-2, Evaluation-Commercial Items, applies to this acquisition. (a) The Government will award a contract resulting from this solicitation to the responsible offeror whose offer conforming to the solicitation will be most advantageous to the Government, price and other factors considered. The following factors shall be used to evaluate offers: (i) technical capability of the service offered to meet the Government requirement; (ii) past performance; and (iii) price. Technical capability and past performance, when combined, are significantly more important than price. (b) A written notice of award or acceptance of an offer, mailed or otherwise furnished to the successful offeror within the time for acceptance specified in the offer, shall result in a binding contract without further action by either party. Before the offer’s specified expiration time, the Government may accept an offer (or part of an offer), whether or not there are negotiations after its receipt, unless a written notice of withdrawal is received before award. (ix) The Offerors to include a completed copy of the provision at FAR clause 52.212-3, Offeror Representations and Certifications-Commercial Items (FEB 2024), with its offer. If the offeror has completed FAR clause 52.212-3 at www.sam.gov, then the offeror does not need to provide a completed copy with its offer. (x) The clause at FAR 52.212-4, Contract Terms and Conditions-Commercial Products and Commercial Services (NOV 2023), applies to this acquisition. Addendum to this FAR clause applies to this acquisition and is attached. (xi) There are no additional contract requirement(s) or terms and conditions applicable to this acquisition. (xii) The Defense Priorities and Allocations System (DPAS) are not applicable to this requirement. (xiii) Responses to this solicitation must include clear and convincing evidence of the offeror’s capability of fulfilling the requirement as it relates to the technical evaluation criteria. The price proposal must include the labor categories, an estimate of the number of hours required for each labor category, fully loaded fixed hourly rate for each labor category, breakdown and rationale for other direct costs or materials, and the total amount. The Unique Entity ID from SAM.gov, the Taxpayer Identification Number (TIN), and the certification of business size must be included in the response. All offerors must have an active registration in the System for Award Management (SAM) www.sam.gov. All quotations must be received by Tuesday, March 12th, 2023 at 9:00 am Eastern Daylight/Standard Time and must reference solicitation number 75N95024Q00163. Responses must be submitted electronically to Rashiid Cummins, Contract Specialist, at rashiid.cummins@nih.gov Fax responses will not be accepted. (xiv) The name and of the individual to contact for information regarding the solicitation: Rashiid Cummins Contract Specialist rashiid.cummins@nih.gov","origin":"extract"},"notice_type":{"code":"k","label":"Combined Synopsis/Solicitation"},"schema_version":1,"solicitation_number":"75N95024Q00163","place_of_performance":{"city":{"name":"Baltimore"},"state":{"code":"MD"},"country":{"code":"USA"}},"product_service_code":"Q301"},{"award":{"date":"2024-03-13","amount":"65869.00","number":"75N95024P000186","awardee":{"raw":"UNIVERSITY OF MARYLAND, COLLEGE PARK College Park MD 20742 USA","name":"UNIVERSITY OF MARYLAND, COLLEGE PARK College Park","location":{"zip":"20742","state":{"code":"MD"},"country":{"code":"USA"}}}},"dates":{"posted":"2024-03-13","award_date":"2024-03-13"},"links":{"sam":"https://sam.gov/workspace/contract/opp/df0bb7c44b7b44d69e4fa171867b1898/view"},"naics":{"codes":["541380"],"primary":"541380"},"title":"Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI","agency":{"office":{"code":"75N950","name":"NATIONAL INSTITUTES OF HEALTH NIDA"},"subtier":{"code":"7529","name":"NATIONAL INSTITUTES OF HEALTH"},"department":{"code":"075","name":"HEALTH AND HUMAN SERVICES, DEPARTMENT OF"},"office_address":{"zip":"20892","city":"Bethesda","state":"MD","country":"USA"},"organization_type":"OFFICE"},"status":{"active":false,"archive_date":"2024-03-28","archive_type":"auto15"},"contacts":[{"name":"Rashiid Cummins","role":"primary","email":"rashiid.cummins@nih.gov"}],"base_type":{"code":"k","label":"Combined Synopsis/Solicitation"},"notice_id":"df0bb7c44b7b44d69e4fa171867b1898","provenance":{"extract":{"url":"https://s3.amazonaws.com/falextracts/Contract%20Opportunities/Archived%20Data/FY2024_archived_opportunities.csv","etag":"\"d582488fe153a9f11bf629913d176ffc-137\"","fetched_at":"2026-09-16T19:07:39.720164Z","row_sha256":"9d96e881756a92592aec32764b7f870edd0a7df3c9d6fb0c42e7b9cfe8d54614","last_modified":"2026-09-13T14:47:40Z"},"updated_at":"2026-09-16T19:07:39.720164Z","first_seen_at":"2026-09-16T19:07:39.720164Z"},"notice_type":{"code":"a","label":"Award Notice"},"schema_version":1,"solicitation_number":"75N95024Q00163","place_of_performance":{"city":{"name":"Baltimore"},"state":{"code":"MD"},"country":{"code":"USA"}},"product_service_code":"B524"}],"due_at":"2024-03-12T13:00:00Z","due_date":"2024-03-12","closes_at":"2024-03-12T13:00:00Z","awardable":false,"dept_key":"d-075","dept_name":"HEALTH AND HUMAN SERVICES, DEPARTMENT OF","sub_key":"s-7529","sub_name":"NATIONAL INSTITUTES OF HEALTH","office_key":"o-75N950","office_name":"NATIONAL INSTITUTES OF HEALTH NIDA","state":"MD","county":"24510","county_name":"City of Baltimore","city":"2404000","city_name":"Baltimore","country":"USA","winner_key":"NPU8ULVAAS23","amount":"65869.00","linked_awards":3,"cancelled":false,"archived":false,"updated_at":"2026-09-16T21:18:12.857524Z","principal_notice_id":"4661d0778ec94f0f8452bf6c5a6f6e11","description":{"text":"(i) This is a combined synopsis/solicitation for commercial items prepared in accordance with the format in Subpart 12.6 as supplemented with additional information included in this notice. This announcement constitutes the only solicitation; proposals are being requested and a written solicitation will not be issued. (ii) The solicitation number is 75N95024Q00163 and the solicitation is issued as a request for quotation (RFQ). This acquisition is for a commercial item or service and is conducted under the authority of the Federal Acquisition Regulation (FAR) Part 13—Simplified Acquisition Procedures; FAR Subpart 13.5—Simplified Procedures for Certain Commercial Items; and FAR Part 12—Acquisition of Commercial Items and is not expected to exceed the simplified acquisition threshold. THIS IS A NON-COMPETITIVE (NOTICE OF INTENT) COMBINED SYNOPSIS SOLICITATION TO AWARD A CONTRACT OR PURCHASE ORDER WITHOUT PROVIDING FOR FULL OR OPEN COMPETITION (INCLUDING BRAND-NAME). The National Institute on Drug Abuse (NIDA), Office of Acquisition (OA), on behalf of the National Institute on Aging (NIA), intends to negotiate and award a purchase order without providing for full and open competition (including brand-name) to University of Maryland for Development of harmonic analysis and machine learning-based approaches for magnetic resonance parameter estimation and for data fusion in MRI. This acquisition is conducted as non-competitive for a commercial item or service and is conducted pursuant to FAR 13.106-(b)(1). (iii) The solicitation document and incorporated provisions and clauses are those in effect through Federal Acquisition Circular (FAC) Number 2024-03, with an effective date February 23, 2024. (iv) The associated NAICS code is 541380 and the small business size standard is $19 million. This requirement has no set-aside restrictions. (v) Statement of Work: See SOW attached. (vi) The Government anticipates award of a firm fixed-price purchase order for this acquisition. The period of performance is 3/15/2024 – 8/31/2024. (vii) The provision at FAR 52.252-1, Solicitation Provisions Incorporated by Reference (Feb 1998), applies to this acquisition. This solicitation incorporates one or more solicitation provisions by reference, with the same force and effect as if they were given in full text. Upon request, the Contracting Officer will make their full text available. The offeror is cautioned that the listed provisions may include blocks that must be completed by the offeror and submitted with its quotation or offer. In lieu of submitting the full text of those provisions, the offeror may identify the provision by paragraph identifier and provide the appropriate information with its quotation or offer. Also, the full text of a solicitation provision may be accessed electronically at these addresses: https://www.acquisition.gov/browse/index/far https://www.hhs.gov/grants/contracts/contract-policies-regulations/hhsar/index.html (End of provision) The following provisions apply to this acquisition and are incorporated by reference: FAR 52.204-7 System for Award Management (OCT 2018) FAR 52.204-16 Commercial and Government Entity Code Reporting (AUG 2020) FAR 52.212-1 Instructions to Offerors--Commercial Items (SEPT 2023) FAR 52.212-3 Offeror Representations and Certifications – Commercial Items (FEB 2024) FAR 52.222-22 Previous Contracts and Compliance Reports (FEB 1999) FAR 52.222-52, Exemption from Application of the Service Contract Labor Standards to Contracts for Certain Services-Certification (May 2014) FAR 52.227-14 Rights in Data-General (MAY 2014) HHSAR 352.239-73 Electronic and Information Technology Accessibility Notice (December 18, 2015) The clause at FAR 52.252-2, Clauses Incorporated by Reference (Feb 1998), applies to this acquisition. This contract incorporates one or more clauses by reference, with the same force and effect as if they were given in full text. Upon request, the Contracting Officer will make their full text available. Also, the full text of a clause may be accessed electronically at these addresses: https://www.acquisition.gov/browse/index/far https://www.hhs.gov/grants/contracts/contract-policies-regulations/hhsar/index.html (End of clause) The following clauses apply to this acquisition and are incorporated by reference: FAR 52.204-13 System for Award Management Maintenance (OCT 2018) FAR 52.204-18 Commercial and Government Entity Code Maintenance (AUG 2020) FAR 52.212-4 Contract Terms and Conditions Commercial Items (NOV 2023) HHSAR 352.222-70 Contractor Cooperation in Equal Employment Opportunity Investigations (December 18, 2015) The following provisions and clauses apply to this acquisition and are incorporated as an attachment. Offerors MUST complete the provisions at 52.204-24 and 52.204-26 and submit completed copies as separate documents with their proposal. FAR 52.204-24 Representation Regarding Certain Telecommunications and Video Surveillance Services or Equipment (NOV 2021) FAR 52.204-26 Covered Telecommunications Equipment or Services-Representation (OCT 2020) FAR 52.212-5, Contract Terms and Conditions Required to Implement Statutes or Executive Orders-Commercial Items (FEB 2024) Invoicing Instructions with IPP (viii) The provision at FAR clause 52.212-2, Evaluation-Commercial Items, applies to this acquisition. (a) The Government will award a contract resulting from this solicitation to the responsible offeror whose offer conforming to the solicitation will be most advantageous to the Government, price and other factors considered. The following factors shall be used to evaluate offers: (i) technical capability of the service offered to meet the Government requirement; (ii) past performance; and (iii) price. Technical capability and past performance, when combined, are significantly more important than price. (b) A written notice of award or acceptance of an offer, mailed or otherwise furnished to the successful offeror within the time for acceptance specified in the offer, shall result in a binding contract without further action by either party. Before the offer’s specified expiration time, the Government may accept an offer (or part of an offer), whether or not there are negotiations after its receipt, unless a written notice of withdrawal is received before award. (ix) The Offerors to include a completed copy of the provision at FAR clause 52.212-3, Offeror Representations and Certifications-Commercial Items (FEB 2024), with its offer. If the offeror has completed FAR clause 52.212-3 at www.sam.gov, then the offeror does not need to provide a completed copy with its offer. (x) The clause at FAR 52.212-4, Contract Terms and Conditions-Commercial Products and Commercial Services (NOV 2023), applies to this acquisition. Addendum to this FAR clause applies to this acquisition and is attached. (xi) There are no additional contract requirement(s) or terms and conditions applicable to this acquisition. (xii) The Defense Priorities and Allocations System (DPAS) are not applicable to this requirement. (xiii) Responses to this solicitation must include clear and convincing evidence of the offeror’s capability of fulfilling the requirement as it relates to the technical evaluation criteria. The price proposal must include the labor categories, an estimate of the number of hours required for each labor category, fully loaded fixed hourly rate for each labor category, breakdown and rationale for other direct costs or materials, and the total amount. The Unique Entity ID from SAM.gov, the Taxpayer Identification Number (TIN), and the certification of business size must be included in the response. All offerors must have an active registration in the System for Award Management (SAM) www.sam.gov. All quotations must be received by Tuesday, March 12th, 2023 at 9:00 am Eastern Daylight/Standard Time and must reference solicitation number 75N95024Q00163. Responses must be submitted electronically to Rashiid Cummins, Contract Specialist, at rashiid.cummins@nih.gov Fax responses will not be accepted. 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