SPECIAL NOTICE
99 -- AI in Medical Imaging (AIMI), Acquisition of Large Datasets-Opportunity at the Frederick National Laboratory for Cancer Research
- Notice Date
- 5/26/2022 11:56:34 AM
- Notice Type
- Special Notice
- NAICS
- 541714
— Research and Development in Biotechnology (except Nanobiotechnology)
- Contracting Office
- NIH National Cancer Institute Rockville MD 20850 USA
- ZIP Code
- 20850
- Solicitation Number
- S22-068
- Response Due
- 6/14/2022 2:00:00 PM
- Point of Contact
- Connor Cigrang
- E-Mail Address
-
connor.cigrang@nih.gov
(connor.cigrang@nih.gov)
- Description
- AI in Medical Imaging (AIMI), Acquisition of Large Datasets-Opportunity at the Frederick National Laboratory for Cancer Research Description � National Institutes of Health, National Cancer Institute, Frederick National Laboratory for Cancer Research Opportunities-Special Notice: This Special Notice is not a formal Invitation for Bid (IFB), Request for Proposal (RFP), Request for Quotation (RFQ) nor any type of Solicitation for offers. In accordance with FAR 15.201(d), this Special Notice is intended FOR INFORMATIONAL PURPOSES ONLY in order to publicize the requirements of the Frederick National Laboratory for Cancer Research (FNLCR). The FNLCR is a Government-Owned Contractor-Operated (GOCO) Federally Funded Research and Development Center (FFRDC) located at Fort Detrick, Maryland. The FNLCR partners with university, government, and corporate scientists to speed the translation of laboratory research into new diagnostic tests and treatments for cancer and AIDS. FNLCR is a multi-program laboratory currently operated by Leidos Biomedical Research Inc. (Leidos Biomed) for the National Cancer Institute (NCI) under Prime Contract No. 75N91019D00024, which provides Operations and Technical Support (OTS) for the Frederick National Lab. The Government assumes no liability for reimbursement for any effort or associated costs to respond, nor for any information provided as a result of this notice as no information is being requested. Please be advised that any submissions provided despite the aforementioned notice that no information is requested become Government property and will not be returned, nor will there be any ensuing discussions or debriefings. Responses submitted to this notice are not offers and cannot be accepted by the U.S. Government to form a binding contract. It is the responsibility of the interested parties to monitor this site and any sites referenced herein for additional information pertaining to business opportunities with the FNLCR, if any. Description of Work: Large datasets from the existing standard of care radiology practice, along with companion clinical data, are needed for the training and development of ML/AI algorithms by the research community.� The Subcontractor must understand and provide the following: Datasets will be shared publicly Datasets must be approved for public distribution by the originating site(s) Datasets should not be currently and/or previously been shared in a public repository Datasets cannot carry any restriction on the use of the data Datasets should be comprised of high-quality standard of care CT, PET/CT, or MRI DICOM images Datasets should be comprised of one or two types of cancer data Datasets must provide demographic and clinical information Imaging data must be de-identified of PHI and PII according to the HIPAA Safe Harbor Method Clinical data must be de-identified of PHI and PII according to the HIPAA Safe Harbor Method Connection between clinical and image data needs to be maintained Datasets that contain image labels, markups, and/or annotations are preferred Support of data transfer Data quality assurance and integrity Provide subject matter expertise Leidos Biomedical Research, Inc.� POC: If you are interested in obtaining the solicitation, please contact Connor Cigrang, Subcontracts Administrator, at �connor.cigrang@nih.gov BY 5PM, EST, May 27th, 2022 For information concerning other opportunities with the FNLCR, please refer to: https://frederick.cancer.gov/workwithus/solicitations
- Web Link
-
SAM.gov Permalink
(https://sam.gov/opp/bd144d43724c4c48bed99cbec1f192c8/view)
- Record
- SN06339572-F 20220528/220526230057 (samdaily.us)
- Source
-
SAM.gov Link to This Notice
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