Description:
Fast-Track proposals will NOT be accepted.
Direct-to-Phase II proposals will NOT be accepted.
Number of anticipated awards: 3-5
Budget (total costs, per award):
Page 88
Phase I: up to $400,000 for up to 12 months
Phase II: up to $2,000,000 for up to 2 years
PROPOSALS THAT EXCEED THE BUDGET OR PROJECT DURATION LISTED ABOVE MAY NOT BE FUNDED.
Summary
Oncology data science and analytics is a burgeoning area of artificial intelligence (AI) and machine learning (ML)
technologies that have fueled interest across the industrial and academic sectors. During the past few years, several startups
and large companies have focused on AI/ML technologies with the aim of reducing complexities in clinical workflow or
increasing accuracy in detection, diagnosis, and treatment of cancer. While tremendous amounts of data are generated
through clinical practice, significant gaps remain to leverage the data for device development and evaluation, including: 1)
generation/acquisition of patient outcome data; 2) truthing of images by clinicians; 3) correlation of multi-modal imaging,
comprehensive clinical, and genomic data in common repositories; 4) extraction of information from unstructured electronic
health records (EHR) data; and 5) availability of clinically infrequent variants. This topic supports an unmet need for the
development of large, well-curated, and statistically robust datasets that can be used for the evaluation of cancer medical
devices subject to regulation by Center for Devices and Radiological Health (CDRH) of the Food and Drug Administration
(FDA). Datasets that may be used to develop new devices as a measure of device effectiveness or performance, and support
regulatory decision-making may be eligible for CDRH’s Medical Device Development Tools (MDDT) program. A tool
eligible for consideration by the MDDT Program is one that reduces the regulatory burden of industry and the FDA.
CDRH’s mission is to protect and promote public health by assuring that patients and providers have timely and continued
access to safe, effective, and high-quality medical devices. To qualify a dataset as an MDDT, CDRH evaluates the dataset
and concurs with the available supporting evidence that the dataset produces scientifically plausible measurements and
works as intended within the specified context of use. More information about the FDA’s MDDT Program can be found
here. CDRH’s MDDT program collaboration with the NCI SBIR Development Center can help incentivize the small
business community to develop and qualify innovative tools for oncology-related regulatory decision-making. These tools
can be sold to industry or academia developing new device technologies that would benefit from using the MDDT in product
development and evidence generation for a regulatory submission, thus stimulating and supporting translation of innovative
devices to the clinic. Given these similar areas of interest, FDA CDRH and NCI SBIR have developed this joint contract
topic to support innovation across our overlapping communities.
