Solicitation: 75N91019R00017
The goal of this acquisition is to identify biomedical computing in support of, but not limited to, the ongoing epidemiology and genetic research programs, conducted in the Branches and Laboratories in DCEG which include domestic and international studies with diverse study designs in epidemiology and genetics research including prospective cohort studies, case-control studies, family studies, and randomized clinical trials. These studies span several geographic areas (potentially in any continent), are of varying size and complexity, and include dense, high-dimensional data on exposures, endpoints, clinical information, and biomarkers from molecular technologies.
Activities performed by the Contractor shall include, but are not limited to:
- Establish a consistent method of invoicing and reporting that tracks labor hours to a study/project identifier and to the requestor and provides detailed reports of the work completed within the period of performance. The minimum level of information that shall be required is defined in the Additional Business Proposal Instructions. This method shall be flexible to accommodate for any changes to NIH, NCI, DCEG business needs that may occur in the future; including, but not limited to, changes to the process of submitting invoices using web-based systems.
- Establish a method for data and knowledge transfer from incumbent contract, as required.
- Establish a method to allow DCEG investigators and staff access to status reports and invoices for contract-related charges as real-time as technically feasible, as discussed with the COR. This method shall be flexible to accommodate for any changes to NIH, NCI, DCEG accounting systems or processes that may occur in the future….
Activities performed by the Contractor shall include, but are not limited to:
- Transition all activities and services from the incumbent contractor.
- Provide data modeling, acquisition and management services for studies with diverse variables, clinical and laboratory data, including environmental exposure (radiation, nutrition, microbial, hormonal, and others), occupational exposure/industrial hygiene parameters, demographics, medical history (i.e. clinical signs, imaging), and high-dimensional molecular data from biospecimens. It is expected that data will increase in size and complexity due to ongoing data collection efforts and additional data generated from molecular technologies (e.g. sequencing, tissue imaging). This shall correspond with scalable computational infrastructure, when possible, leveraging Cloud Computing made available by NIH programs such as STRIDES).
